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6202.0 - Labour Force, Australia, Mar 2007  
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 12/04/2007   
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FORTHCOMING CHANGES


IMPROVED ESTIMATION METHOD

As announced in the previous issue of this publication, in June 2007 the ABS will introduce an improved method of estimation for the Labour Force Survey (LFS). The new method, known as composite estimation, is more efficient than the current estimation method. That is, the composite estimator achieves a given level of standard error at lower cost than the current estimator. This note provides further information on the new method's effect on LFS estimates.


The new estimation method will be introduced with the release of May 2007 labour force statistics on 7 June 2007 in Labour Force, Australia (cat. no. 6202.0). At the same time, the ABS will release revised historical LFS statistics based on the new estimation method, back to April 2001. An updated standard error model will also be introduced to reflect the composite estimation method.


The change in estimation method will have an impact on all LFS statistical releases (publications, spreadsheets, and data cubes). Detailed information on statistical impacts will be provided in Information Paper: Forthcoming Changes to Labour Force Statistics (cat. no. 6292.0) to be released on 27 April 2007. This paper will be available free from the ABS web site <http://www.abs.gov.au> (Themes - People, Labour).



REVIEW OF CURRENT ESTIMATION METHOD

The current LFS estimator derives estimates of the number of people employed, unemployed and not in the labour force by applying expansion factors (or weights) to the LFS sample responses for the reference month, so that the weights add up to independent estimates of the civilian population aged 15 years and over (called population benchmarks). The benchmarks are classified by geographic area, age and sex.


The ABS has been investigating composite estimation methods for several years. Some of the ABS research findings are available in the article 'Can Labour Force Estimates be Improved using Matched Sample Estimates?' in the May 1998 issue of Australian Economic Indicators (cat. no. 1350.0), available free from the ABS web site.



NEW ESTIMATION METHOD

The composite estimation method being implemented is a modified version of a Best Linear Unbiased Estimator. The new composite estimator will combine data collected in the previous six months with the current month's data to produce the current month's estimates. Technical details about the method can be found in Research Paper: The impact of rotation patterns and composite estimation on survey outcomes, MAC Paper, 1998 (cat. no. 1352.0.55.017). The method is similar to that being used for labour force surveys in several other countries.


In the LFS, dwellings remain in the survey for eight consecutive months, with one-eighth of the sample being replaced each month. This means there is a seven-eighth overlap in the dwelling samples in adjacent months, a six-eighth overlap in the samples two months apart, and so on. The composite estimator exploits the high correlation between overlapping samples across the current and immediately preceding months to achieve lower standard errors than the current estimator.



EFFECT ON STANDARD ERRORS

For the duration of the current LFS sample design, the advent of composite estimation will result in lower standard errors on LFS estimates than those currently achieved. The reduction in standard error at the Australia level is expected to be approximately 10% for employment level and monthly movement estimates, and 5% for unemployment estimates (levels and monthly movements). A similar result is expected for states and territories.


In line with standard ABS practice, a new LFS sample design will be introduced progressively between November 2007 and June 2008, based on results from the 2006 Population Census. Standard errors expected to be achieved under the new sample design will depend on a number of factors including available budget, cost of enumeration, and the variability of labour market characteristics in the population.



EFFECT ON LABOUR FORCE ESTIMATES

The new composite estimator produces estimates of employment and unemployment which are slightly lower on average than those produced by the current estimator. This effect applies for original, seasonally adjusted and trend series.


Analysis of labour force data for the period April 2001 to January 2007 shows that for seasonally adjusted series at the Australia level, employment estimates are 0.07% lower on average under composite estimation than under the current estimator. Unemployment estimates are 1.56% lower, whilst the unemployment rate is 0.08 percentage points lower (on average). The participation rate is 0.10 percentage points lower on average. This effect can be seen in the graphs on page 5.


The same analysis shows that for the states and territories seasonally adjusted series:

  • Employment estimates are 0.06-0.13% lower on average. The exceptions are Western Australia, where employment estimates are on average the same, and the Northern Territory, where employment estimates are 0.24% higher under composite estimation.
  • Unemployment estimates are 0.15-3.20% lower.
  • The unemployment rate is 0.04-0.18 percentage points lower on average, with the exception of Tasmania where the unemployment rate is on average the same.
  • The participation rate is 0.03-0.13 percentage points lower on average, with the exception of the Northern Territory, where the participation rate is 0.03 percentage points higher under composite estimation.

This pattern of slightly changed levels of employment and unemployment under composite estimation is due to the 'time in survey' effect which has long been observed in the LFS. This effect refers to the tendency of the incoming one-eighth sub-sample each month to produce slightly different estimates than the other sub-samples that have been in the sample for some months. The composite estimator changes the impact of the 'time in survey' effect on survey estimates because it puts less weight on the dwellings that are new in the sample.


The ABS has analysed the 'time in survey' effect over the period April 2001 to January 2007. For Australia, on average 59.94% of people in their first month in survey were employed, compared with 59.43% of people in their last month in survey. The proportion of people not in the labour force correspondingly increased on average from 36.24% of people in their first month in survey to 37.11% of people in their last month in survey. At the state/territory level, the effect varies. In most, the proportion of employed persons and unemployed persons decreases as time in survey increases. However, in the Northern Territory, the proportion of employed persons actually increases as time in survey increases. This explains why the composite estimate for employment in the Northern Territory is slightly higher on average than the current estimate.

Employed Persons - Australia, Seasonally Adjusted
Graph: Employed Persons - Australia, Seasonally Adjusted


Unemployed Persons - Australia, Seasonally Adjusted
Graph: Unemployed Persons - Australia, Seasonally Adjusted


Unemployment Rate - Australia, Seasonally Adjusted
Graph: Unemployment Rate - Australia, Seasonally Adjusted


Participation Rate - Australia, Seasonally Adjusted
Graph: Participation Rate - Australia, Seasonally Adjusted


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