Characteristics of Recent Migrants, Australia methodology

This publication contains results from the 2019 Characteristics of Recent Migrants Survey (CoRMS), conducted throughout Australia in November 2019 as a supplement to the monthly Labour Force Survey (LFS).

CoRMS provides data about the labour force status and other characteristics of recent migrants and temporary residents, including:

• general demographic and employment characteristics of recent migrants and temporary residents,
• the type of visa held by recent migrants and temporary residents on arrival in Australia,
• education and employment before and after arriving in Australia,
• any difficulties experienced finding work since migration and
• proficiency in English.
   

The publication Labour Force, Australia (cat. no. 6202.0) contains information about survey design, sample redesign, scope, coverage and population benchmarks relevant to the monthly LFS, which also apply to supplementary surveys. It also contains definitions of demographic and labour force characteristics.

The conceptual framework used in Australia's LFS aligns closely with the standards and guidelines set out in Resolutions of the International Conference of Labour Statisticians. Descriptions of the underlying concepts and structure of Australia's labour force statistics, and the sources and methods used in compiling these estimates, are presented in Labour Statistics: Concepts, Sources and Methods, Feb 2018 (cat. no. 6102.0.55.001).)

In July 2014, the LFS survey questionnaire underwent a number of developments. For further information see Information Paper: Questionnaire Used in the Labour Force Survey, July 2014.

The scope of CoRMS is restricted to people aged 15 years and over who were usual residents of private dwellings, excluding:

• members of the permanent defence forces
• certain diplomatic personnel of overseas governments, customarily excluded from the Census of Population and Housing and estimated resident populations
• overseas residents in Australia
• members of non-Australian defence forces (and their dependants)
• people living in Indigenous communities in Australia
• people living in non-private dwellings such as hotels, university residences, boarding schools, hospitals, retirement homes, homes for people with disabilities, and prisons.
   

To be eligible to receive the CoRMS, people had to:

• be born overseas (excluding New Zealand)
• not be Australian or New Zealand citizens before arrival
• have arrived in Australia after 2009
• if arrived in 2019, plan to stay longer than 12 months
• be aged 15 years or over on arrival.
   

In the LFS, coverage rules are applied which aim to ensure that each person is associated with only one dwelling and has only one chance of selection in the survey. See Labour Force, Australia (cat. no. 6202.0) for more details.

Data from the CoRMS is available by State, Greater Capital City Statistical Area, Section of State, Remoteness area and Statistical Area Level 4, subject to confidentiality constraints. Geography has been classified according to the Australian Statistical Geography Standard (ASGS), July 2016. For a list of these publications see the ABS Geography Publications page.

Approximately 92% of the selected households were fully responding to the Monthly Population survey. Of these, 2,887 complete interviews were obtained from recent migrants and temporary residents.

Information was mainly collected through interviews conducted over a two-week period in November 2019. Interviews were conducted face-to-face or over the telephone, using computer assisted interviewing, while some respondents were able to provide certain information over the Internet via a self-completed form.

In CoRMS, 'any responsible adult' respondent methodology is predominantly used. This involves one adult in the household providing answers to the questionnaires for people in the household who are in-scope of CoRMS, and are related. Where the 'any responsible adult' is not related to the migrant, a personal interview with the migrant is conducted. This is also known as self-reporting.

Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each enumerated person. The weight is a value which indicates how many people in the population are represented by the sample person.

The first step in calculating weights for each unit is to assign an initial weight, which is the inverse of the probability of the unit being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 300, then the person would have an initial weight of 300 (that is, they represent 300 people).

The initial weights are then calibrated to align with independent estimates of the population, referred to as benchmarks. The population included in the benchmarks is the survey scope. This calibration process ensures that the weighted data conform to the independently estimated distribution of the population described by the benchmarks rather than to the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons which may occur due to either the random nature of sampling or non-response.

The survey was benchmarked to the estimated resident population (ERP) aged 15 years and over living in private dwellings and non-institutionalised special dwellings in each state and territory. People living in Indigenous communities were excluded.

In 2016 the weighting methodology was modified to include ERP Migration statistics from Migration, Australia (cat. no. 3412.0) as part of the benchmark process. This weighting method was repeated in 2019.

Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristics of interest.

To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.

All sample surveys are subject to error which can be broadly categorised as either: sampling error or non-sampling error. Relative standard error (RSE) for estimates and margin of error (MOE) for proportions are available in the data tables. Estimates with high RSEs are annotated and caution is advised when using these values. For more information refer to the Technical Note.

The ABS has previously conducted a survey of recent migrants in 1984, 1987, 1990, 1993, 1996, 1999, 2004, 2007, 2010, 2013 and 2016. While the ABS seeks to maximise consistency and comparability over time by minimising changes to the survey, sound survey practice requires ongoing development to maintain the integrity of the data. When comparing data over time the following changes need to be considered:

• Labour Force Status and Other Characteristics of Migrants Surveys conducted up to and including November 1996 were restricted to migrants who arrived in Australia after 1970, were aged 18 years and over on arrival, and had obtained permanent Australian resident status.
• For November 1999, the survey was restricted to migrants who arrived in Australia after 1980, were aged 18 years and over on arrival, and had obtained permanent Australian resident status.
• For November 2004, the survey included migrants aged 15 years and over on arrival, who arrived in Australia after 1984 who had obtained permanent Australian resident status, as well as people who were temporary residents of Australia for 12 months or more.
• For November 2007, November 2010 and November 2013, the surveys have included migrants who arrived in Australia in the last 10 years (since 1997, 2000 and 2003 respectively), were aged 15 years and over on arrival, who had obtained permanent Australian resident status, as well as people who were temporary residents of Australia for 12 months or more. In 2007, people born in New Zealand, those holding New Zealand citizenship and those who held Australian citizenship before their arrival in Australia were excluded.
• In 2010 and 2013, people holding New Zealand citizenship and those who held Australian citizenship before their arrival in Australia were excluded, while other people born in New Zealand were included.
• In 2016, New Zealand born people were excluded from the survey.
• In 2016 the weighting methodology was modified to include ERP Migration statistics as part of the benchmark process.
   

Revisions are made to population benchmarks for the LFS after each five-yearly Census of Population and Housing. The latest revision based on the 2016 Census of Population and Housing has been in use since November 2018. See Labour Force, Australia (cat. no. 6202.0) for more information.

As announced in the June 2012 issue of Australian Demographic Statistics (cat. no. 3101.0), intercensal error between the 2006 and 2011 Censuses was larger than normal due to improved methodologies used in the 2011 Census Post Enumeration Survey. The intercensal error analysis indicated that previous population estimates for the base Census years were over-counted. An indicative estimate of the size of the over-count is that there should have been 240,000 fewer people at June 2006, 130,000 fewer in 2001 and 70,000 fewer in 1996. As a result, Estimated Resident Population estimates have been revised for the last 20 years rather than the usual five. Consequently, estimates of particular populations derived since CoRMS 2013 may be lower than those published for previous years as the CoRMS estimates have not been revised. Therefore, caution should we used when comparing CoRMS 2016 and CoRMS 2019 estimates with previous years.

Estimates from the CoRMS may differ from the estimates produced from other ABS collections, for several reasons. The CoRMS is a sample survey and its results are subject to sampling error. Results may differ from other sample surveys, which are also subject to sampling error. Users should take account of the relative standard errors (RSEs) on estimates and those of other survey estimates where comparisons are made.

Differences may also exist in the scope and/or coverage of the CoRMS compared to other surveys. Differences in estimates, when compared to the estimates of other surveys, may result from different reference periods reflecting seasonal variations, non-seasonal events that may have impacted on one period but not another, or because of underlying trends in the phenomena being measured.

Finally, differences can occur as a result of using different collection methodologies. This is often evident in comparisons of similar data items reported from different ABS collections where, after taking account of definition and scope differences and sampling error, residual differences remain. These differences are often the result of the mode of the collections, such as whether data are collected by an interviewer or self-enumerated by the respondent and whether the data are collected from the person themselves or from a proxy respondent. Differences may also result from the context in which questions are asked, i.e. where in the interview the questions are asked and the nature of preceding questions. The impacts on data of different collection methodologies are difficult to quantify. As a result, every effort is made to minimise such differences.

Since the CoRMS is conducted as a supplement to the LFS, data items collected in the LFS are also available in CoRMS. However, there are some important differences between the two surveys. The CoRMS sample is a subset of the LFS sample (see the Introduction of these Explanatory Notes) and has a response rate which is slightly lower than the LFS response rate for the same period. Also, the scope of the CoRMS differs slightly to the scope of the LFS (refer to the Scope section above). Due to these differences between the samples, the CoRMS data are weighted as a separate process to the weighting of LFS data.

Differences may therefore be found in the estimates collected in the LFS and published as part of the CoRMS, when compared with estimates published in the November 2019 issue of Labour Force, Australia (cat. no. 6202.0). It is also impracticable to obtain information relating to the labour force status of people before migration according to the strict definitions used in the monthly LFS. It is for this reason that 'Has had a job since arriving in Australia' and 'Has not had a job since arriving in Australia' are used to describe previous labour force status, while 'employed', 'unemployed' and 'not in the labour force' are used to describe labour force status as at November 2019.

Estimates from CoRMS will differ from estimates from the Microdata: Australian Census and Migrants Integrated Dataset, 2016 (ACMID). The ACMID 2016 relates to people who responded to the 9 August 2016 Census of Population and Housing and had a permanent visa record on the Department of Home Affairs (Home Affairs) Permanent Migrant Settlement Dataset with a date of arrival between 1 January 2000 and 9 August 2016. ACMID estimates were a result of integrating the data from these two data sources and calibrating the linked records to known population totals from Home Affairs dataset.

Estimates from CoRMS will also differ from estimates from the Microdata: Australian Census and Temporary Entrants Integrated Dataset, 2016 (ACTEID). The ACTEID 2016 relates only to temporary entrants who were present in Australia on 9 August 2016 (Census Night) and integrates their Census data with temporary visa holder data from Home Affairs.

The Department of Home Affairs is the main holder of stocks and flow data on migrants by visa (e.g. Migration Program). Due to differences in collection objectives and definitions, data from CoRMS are not comparable with Home Affairs data. For more information on the Migration Program and Home Affairs statistics, refer to their website.

A number of data cubes (spreadsheets) containing all tables produced for this publication are available from the Data downloads section of the publication. The data cubes present tables of estimates and proportions, and their corresponding measures of error.

The ABS no longer formally utilises a standard classification for Main English Speaking Country (MESC). Therefore, from 2019 onward, the data item 'Country of birth (MESC)' will not be available as part of this publication and has not been included in the tables available for download. As a result, Tables 3, 6, 7, 9, 10, 11, 12, 14, 16 and 18 have been modified accordingly and two tables (Table 18 and 19 in the previous iteration in 2016) have been removed.

For users who wish to undertake more detailed analysis of the data, the survey microdata will be released through the TableBuilder product (see Microdata: Characteristics of Recent Migrants, Australia (cat. no. 6250.0.25.002) for more detail). Microdata can be used by approved users to produce customised tables and analysis from the survey data. Microdata products are designed to ensure the integrity of the data whilst maintaining the confidentiality of the respondents to the survey. More information can be found at How to Apply for Microdata.

Customised statistical tables to meet individual requirements can be produced on request. These are subject to confidentiality and sampling variability constraints which may limit what can be provided. Enquiries on the information available and the cost of these services should be made to the National Information and Referral Service on 1300 135 070.

Two types of error are possible in estimates based on a sample survey:

• non-sampling error
• sampling error
   

Non-sampling error is caused by factors other than those related to sample selection. It is any factor that results in the data values not accurately reflecting the true value of the population.

It can occur at any stage throughout the survey process. Examples include:

• selected people that do not respond (e.g. refusals, non-contact)
• questions being misunderstood
• responses being incorrectly recorded
• errors in coding or processing the survey data
   

Sampling error is the expected difference that can occur between the published estimates and the value that would have been produced if the whole population had been surveyed. Sampling error is the result of random variation and can be estimated using measures of variance in the data.

One measure of sampling error is the standard error (SE). There are about two chances in three that an estimate will differ by less than one SE from the figure that would have been obtained if the whole population had been included. There are about 19 chances in 20 that an estimate will differ by less than two SEs.

This publication reports the relative standard error (RSE) for estimates of counts ('000) and the margin of error (MOE) for estimates of proportions (%).