6202.0 - Labour Force, Australia, Apr 2017 Quality Declaration
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 18/05/2017
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APRIL KEY POINTS
TREND ESTIMATES (MONTHLY CHANGE)
SEASONALLY ADJUSTED ESTIMATES (MONTHLY CHANGE)
IMPACT OF CYCLONE DEBBIE ON ESTIMATES
The damage caused by Cyclone Debbie in Queensland resulted in a marginal increase in the sample loss in the Fitzroy region in April 2017, of less than 20 dwellings. This did not have any observable impact on estimates for Queensland.
ANNUAL SEASONAL RE-ANALYSIS OF QUARTERLY LABOUR FORCE SERIES
The annual seasonal re-analysis of Labour Force series was conducted on estimates up to February 2017 and reflected in the monthly estimates in the March issue. The results will be applied to the quarterly series in the May 2017 issue, to coincide with the next available quarterly data. Improvements in the prior corrections used for quarterly estimates of underemployment and underutilisation will be reflected in revisions to publication tables 20 and 21, and time series spreadsheets 22 and 23.
The quarterly seasonally adjusted employed total, in time series spreadsheet 4 in Labour Force, Australia, Detailed, Quarterly (cat. no. 6291.0.55.003) will also be revised to reflect improved correction factors. This will ensure closer alignment with both the sum of the industry divisions, and the monthly employment estimate.
ONLINE COLLECTION IN THE LABOUR FORCE SURVEY
This issue provides an update on online collection in the Labour Force Survey.
Estimates of changes shown on the front cover and used in the commentary have been calculated using unrounded estimates, and may be different from, but are more accurate than, movement obtained from the rounded estimates. The graphs on the front cover also depict unrounded estimates.
The estimates in this publication are based on a sample survey. Published estimates and movements are subject to sampling variability. Standard errors give a measure of sampling variability. The interval bounded by two standard errors is the 95% confidence interval, which provides a way of looking at the variability inherent in estimates. There is a 95% chance that the true value of the estimate lies within that interval.
For further information about these and related statistics, email <email@example.com> or contact the National Information and Referral Service on 1300 135 070.
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