There has been an abrupt shift in consumer psychology which has implications for government policy, the Reserve Bank, and business decision makers. Economic pessimism has increased and the level of belief in climate change has lifted.
These changes seem to be at odds with the federal government’s “sticking to our policy” mantra. The heightened expectation of a rise in unemployment is inconsistent with the Reserve Bank’s hope for a decline in the unemployment rate to 4.5%. Other shifts in consumer psychology are more positive and provide an opportunity to boost consumer spending growth.
The level of belief in imminent climate change in late 2019 is the second-highest recorded and is slightly higher than in 2007, when John Howard lost his seat in parliament and his government lost office.
The federal government and many businesses need to take more decisive action on climate change to satisfy voter (and customer) expectations.
For several years, prominent Australian economist Ross Garnaut has warned of “the great Australian complacency” which has significantly slowed Australia’s economic growth rate. That description clearly also applies to the issue of climate change.
As the new decade dawns, more Australians are experiencing the costs of these policy complacencies.
Our tracking survey update was in field in November and early December 2019.
A summary report is available at foreseechange.com.au.
On May 8th 2018 the Bureau’s forecast for cumulative rainfall in Melbourne over the following five days was between 35mm and 144mm. The actual received was 39mm. This was, of course, within that wide band but towards the lower end. The mean of the range was 89.5mm so on that basis, the forecast error was quite large. That may have been disappointing for farmers but a relief for emergency services planners. The largest forecast error for any of those days was for the Friday: the forecast was for 25 to 80, but only 8.4 was received.
It would be helpful for planners to have a probability distribution. For example, was the upper limit of the five day forecast (144mm) a one in 100 chance or a one in ten chance?
This forecasting error might be understandable if it was an isolated incident. Melbourne is a difficult location to forecast due to high variability. But this was not an isolated incident.
Only a few months earlier, in December 2017, an unprecedented rainfall event was predicted but did not materialise. In January 2015, another such prediction was made and did not materialise.
These seem to be systematic failures rather than random errors, suggesting that the Bureaus models are not sensitive to an important driving force.
What is that driving force? Find out in my book “Forecasting: the essential skills”. It describes these incidents in more detail and contains my suggestion as to what the Factor X is. The book also reviews forecasting skill in economic forecasting and political forecasting as well as weather and climate forecasting.