Tourism Satellite Accounts: quarterly tourism labour statistics, Australia, experimental estimates methodology

Tourism job numbers shown in the Quarterly Tourism Labour Statistics were developed to help explain the impact of COVID-19 on tourism activity. They are currently considered experimental.

A job becomes a tourism-related job when it has a direct impact on tourism activity. A direct impact occurs where there is a direct relationship (physical and economic) between a visitor and the producer of a good or service. Indirect effects of tourism consumption is a broader notion that includes downstream effects of tourism demand and is out of scope for this publication. 

Tourism jobs are not directly observable and assumptions are required to calculate the Quarterly Tourism Labour Statistics. The industries that produce tourism products are identified within the Australian and New Zealand Standard Industrial Classification (ANZSIC). Tourism value added industry ratios are then applied to the tourism industries to derive estimates of tourism employment. Updated ratios are created with each annual Tourism Satellite Account. See the Methodology of the Tourism Satellite Account for details on how the industry ratios are calculated. Updated ratios are applied to the quarterly estimates in September quarter each year and may result in revisions to historical estimates.

The Australian Labour Account provides a conceptual framework through which existing labour market data from different sources can be confronted and integrated, with the aim of producing a coherent and consistent set of aggregate labour market statistics. It incorporates labour input aggregates (persons, jobs and hours) which describe supply and demand in the labour market, as well as labour related payments (such as income and costs). The framework covers all types of employment including employees, self-employment and contributing family workers. Job counts represent the number of jobs on the last day of the reference period e.g. 31 March in the March quarters.

The concepts and definitions underlying the Australian Labour Account are built on International Labour Organisation fundamentals and expands them to ensure consistency with the System of National Accounts 2008. The result provides a set of core macro-economic labour market variables derived from existing data through data integration, with both an industry focus and time series dimension.

The Methodology section of the Labour Account publication provides a more detailed explanation.

Part-time, full-time, male and female employment ratios are derived for each tourism characteristic and connected industry using ratios derived from Labour Force Survey (LFS) data. These ratios are applied to the tourism labour account filled jobs and main jobs estimates for each tourism industry. The ratios from the May LFS are used to calculate June quarter tourism statistics, August LFS are used to produce September quarter tourism statistics etc.

Several assumptions underlie the compilation of the Quarterly Tourism Labour Statistics. These include:

• Jobs in tourism related industries will generally provide goods and services to both visitors and non-visitors. 

• The contribution tourism activity makes to the economy by industry is equivalent to the contribution tourism activity has to the labour market.

• The structure of the economy generally changes slowly over time, therefore employment generated by tourism in each industry is directly related to value added generated by tourism in the benchmark year. This assumption holds well, except when there are sudden economic shocks that cause structural changes to the economy, e.g., a health pandemic, and/or significant changes in input costs (such as fuel). Ideally, the tourism value added ratios would be updated every quarter in the Quarterly Tourism Labour Statistics to reflect the current situation, however, this is not possible due to data availability issues.

• The distribution of jobs (full-time/part-time, male/female) within the tourism share of a particular industry is consistent with the employment patterns in the Labour Force Survey (LFS) for that particular industry.

Revisions are a necessary and expected part of accounts compilation as data sources and processes are updated and improved over time. As more up-to-date information, such as tourism value added industry ratios, become available after each TSA benchmark process, they will be incorporated into the quarterly tourism labour estimates. 

While the benchmark ratios are currently updated each year, the full suite of information to calculate these ratios does not become available until two years after the reference period. The rapid changes brought about by COVID-19 will result in a higher level of revision than in other periods. For more information on TSA benchmarks, please refer to the Tourism Satellite Account Methodology section.

The Quarterly Tourism Labour Statistics draws on data published in the latest available issue of the Australian Labour Account at the time of compilation. 

From 2021-22, the TSA moved to using the Australian Labour Account for tourism employment estimates. Therefore, the data in this publication will be consistent with the data included the 2021-22 TSA. Both the TSA and Australian Labour Account are subject to revision. The timing of these revisions will result in small differences between the employment estimates in this publication and those shown in the annual TSA.

Every effort is made to minimise the impact of measurement error through robust methods, data confrontation and other quality control processes. However, measurement error is inherent and unavoidable in all statistics. Some possible sources of measurement error in the Quarterly Tourism Labour Statistics include:

• Measurement error from input data (see Labour Account Methodology and annual TSA Methodology).
• Modelling error, which includes errors in modelling assumptions used to construct the Quarterly Tourism Labour Statistics estimates. Care should be taken during times of rapid change as modelling error may increase.