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Shire of Moora

Specific topic notes

Indicators - Estimate Resident Population

Populations are counted and estimated in various ways. The most comprehensive population count available in Australia is derived from the Population and Household Census conducted by the Australian Bureau of Statistics every 5 years.

However the Census count is not the official population of an area. To provide a more accurate population figure which is updated more frequently than every 5 years, the Australian Bureau of Statistics also produces "Estimated Resident Population" (ERP) numbers. Based on population estimates as at 30 June, ERPs take into account people who missed the count on Census night, including people who were temporarily overseas, plus an undercount adjustment for those who did not complete a Census form, and an overcount adjustment for anyone who was double counted.

Estimated Resident Population figures are updated annually taking into account births, deaths, internal and overseas migration. In addition, after every Census, ERP figures for the five previous years are "backcast", using information from the current Census, to ensure the most accurate figures are available.

See the ABS demographic publications, 3101.0 and 3218.0 for further details.

Gross Regional Product (GRP)

The gross domestic product (GDP) is one of the measures of national income and output for a country’s economy. It is the total value of all final goods and services produced in the economy. GDP provides a systematic statistical framework for summarising and analysing economic events, and wealth of an economy.

In Australia, the ABS is responsible for calculating National (GDP) and State (GSP) Gross Product. See ABS Australian National Accounts: National Income, Expenditure and Product(Catalogue Number 5206.0) for more information.

Data source: Australian Bureau of Statistics, Australian National Accounts: National Income, Expenditure and Product, (catalogue number 5206.0)

For the local area this information is synthesized by National Economics using a range of data sources (including ABS labour force survey, tax office and Centrelink datasets) to produce an estimate of the Gross Regional Product of the local economy. GRP is the equivalent of GDP at the local level for a Local Government Area or region, and the calculation method simulates that used for the nation, but is influenced by local characteristics such as types of employment and worker productivity. For more information see National Institute of Economic and Industry Research (NIEIR)

To enable direct comparison between areas of varying size (eg. local, state, national), each year of data is divided by the base reference year and multipled by 100 so that all areas are compared on the same scale. The actual size of the economy, and growth is shown in the box at the left. All data are expressed in constant dollar terms for the reference year (shown on the chart).

Indicators - Unemployment

Please note that the local unemployment data are sourced from Small Area Labour Markets, a quarterly publication by the Department of Employment and Workplace Relations. State and National figures are sourced from the ABS Labour Force Survey (Catalogue number 6202.0). The Department of Employement data uses the labour force survey as a base, and models it to local level using Centrelink data. Local unemployment is updated quarterly in this collection, and while state and national figures are available monthly, these are also updated on the site quarterly to match the time period of the local numbers.

All labour force data are subject to sampling error, as they are derived from a sample survey of approximately 29,000 dwellings nationwide.

All labour force data relate to the civilian population aged 15 years and over.

The definition of unemployment used is the standard ABS and international definition - Unemployed persons are defined as all persons aged 15 years and over who were not employed during the reference week, and either had actively looked for full-time or part-time work at any time in the four weeks up to the end of the reference week and were available for work in the reference week, or were waiting to start a new job within four weeks from the end of the reference week and could have started in the reference week if the job had been available then.

Employed persons are those aged 15 years or over who, during the survey reference week, worked for one hour or more for pay, profit or payment in kind in a job or business, or on a farm; or worked for one hour or more without pay in a family business or on a farm; or who had a job but were not at work for a number of specified reasons; or were employers or self-employed persons who had a job, business or farm, but were not at work.

Indicators - Building approvals

Value of building approval data are sourced from the Australian Bureau of Statistics, Catalogue number 8731.0 – Building Approvals, Australia. This is a monthly publication, with the data here presented quarterly. Data may be revised up to a year after publication.

The value of approval data includes all approved residential building valued at $10,000 or more and all approved non-residential building valued at $50,000 or more. Value of building work excludes the value of land, and also excludes landscaping, but includes site preparation costs. Both new dwellings and alterations and additions to existing dwellings are included in the residential approvals.

Data presented here are the "Original" series, which has not been seasonally adjusted or smoothed to remove anomalies. Seasonal adjustment is not available at a local level, so for comparison purposes the state and national figures shown here are also "Original". Seasonally adjusted and trend figures are more often reported on a national basis by the ABS and the media, so for this reason, the figures shown here may not match those often reported.

Indicators - Retail trade

(not available for local area)

Retail Trade trends are based on estimates of turnover compiled from the monthly Retail Business Survey (RBS) undertaken by the ABS. It estimates of the value of turnover of retail businesses classified by industry, and by state and territory. It is not available for local areas. See ABS Retail Trade catalogue number 8501.0 for more details.

Data source: Australian Bureau of Statistics. Retail Trade , (catalogue number 8501.0)

Indicators - Consumer Price Index (CPI)

(not available for local area)

The Consumer Price Index (CPI) measures quarterly changes in the price of a 'basket' of goods and services which account for a high proportion of expenditure by the CPI population group (i.e. metropolitan households). This 'basket' covers a wide range of goods and services, arranged in the following eleven groups:

  • Food
  • Alcohol and tobacco
  • Clothing and footwear
  • Housing
  • Household contents and services
  • Health
  • Transportation
  • Communication
  • Recreation
  • Education
  • Financial and insurance services.

The Consumer Price Index is measured for Greater Capital City regions only, so the state capital is used as a proxy for the whole state, and the Australia-wide index is correctly termed as the "Weighted average of eight capital cities".

CPI is an index designed to measure change over time. See ABS Consumer Price Index, (catalogue number 6401.0) for more details.

Data source: Australian Bureau of Statistics, Consumer Price Index , (catalogue number 6401.0)

Employment by industry (Census)

Employment data is sourced from the ABS Census. It is the total number of persons employed in an industry sector, within the local area. It is based on the ABS coding of workplace addresses, not on residential location. This dataset should NOT be compared with National Economics modelled datasets on number of workers, which are a more accurate representation and updated every year. Census counts of employment are useful because they can break down to a more detailed level of industry classification than the modelled dataset, and can also present various demographic characteristics of the workers. However it needs to be remembered that they are an undercount of the true employment and exclude

  1. People who didn't state their employment status.
  2. People who have no fixed place of work and therefore are not coded to a workplace address.
  3. People whose workplace address was unable to be coded by the ABS to a valid location.
  4. People who were entirely missed in the Census.

On average, for 2011, Census counts of employment are expected to be a 15% undercount of the true employment in an area, of which 12.5% is due to poor address coding by the ABS in 2011 (coding was significantly worse in 2011 than in the previous 2 Censuses). In some areas it may be as high as 25%. Modelled estimates are also updated annually, while Census data are only updated every 5 years. Please use these Census figures with caution when assessing local employment numbers.

This table presents information at the ANZSIC 1-digit (division) level, with sub-categories available at the 3-digit (group) level. A total of 293 industry categories are available at this level, by clicking on the table entries, or exporting the full version of the table. Only division level data appear in the charts.

Residential location of workers

This dataset is known as Journey to Work, and is derived from Census question 41 – "For the main job held last week, what was the person's workplace address?" With residential address also known, Journey to Work comprises a matrix linking origin (residence) and work destination.

The data presented here in table form show the Statistical Local Area of residence for employed persons who work within Shire of Moora. The map shows the spatial distribution of these workers.

Please note that the workforce in a Local Government Area calculated from Census data is generally considered to be an undercount, due to the number of people whose workplace address was not stated, could not be accurately coded, or stated a non-permanent workplace address ('no fixed place of work'). These people appear in the employment data at their residential location but cannot be coded to a work destination.

In 2011, a record number (over 1 million or 10% of employed persons) have been coded to an undefined work destination which cannot be mapped, and so these are excluded from the working population. For this reason some LGAs may notice an apparent drop in their Census-based workforce numbers between 2006 and 2011. While only 2011 data are presented here, this is most likely the reason.

If comparing work destination information with Method of Travel to work, please note the differing time periods – Workplace address relates to the week prior to Census, while Method of Travel relates to the morning of Census day. This has a negligible effect on the total counts but can explain some of the small numbers of strange LGA-LGA pairings which crop up such as people appearing to travel interstate to work. Some of these may be genuinely Fly-in/Fly-out workers (likely if the work destination is a known mining area), but others may have moved address in the differing timeframes assessed by the two questions.

Work location of residents

This dataset is known as Journey to Work, and is derived from Census question 41 – "For the main job held last week, what was the person's workplace address?" With residential address also known, Journey to Work comprises a matrix linking origin (residence) and work destination.

The data presented here in table form show the Statistical Local Area of work destination for employed persons who live within Shire of Moora. The map shows the spatial distribution of where these residents work.

Please note that not all employed persons can be accurately coded to a workplace address. In 2011, a record number (over 1 million or 10% of employed persons) have been coded to an undefined work destination. These undefined locations are broken down by state, and shown in the table, but they cannot be mapped, as there is no information on the geographic location of work apart from their state.

For this reason, there may be difficulty comparing 2011 work destination data to 2006, and only 2011 data are presented here. This very large increase in undefined workplace location is believed to be due to the change to the new geography standard (ASGS), and the inefficient coding mechanisms used to code to it.

If comparing work destination information with Method of Travel to work, please note the differing time periods – Workplace address relates to the week prior to Census, while Method of Travel relates to the morning of Census day. This has a negligible effect on the total counts but can explain some of the small numbers of strange LGA-LGA pairings which crop up such as people appearing to travel interstate to work. Some of these may be genuinely Fly-in/Fly-out workers (likely if the work destination is a known mining area), but others may have moved address in the differing timeframes assessed by the two questions.

For more information please refer to the data quality statement for Place of Work on the ABS website.

Residents place of work

This data describes the work location (LGA/SLA) of employed residents of the local area. Journey to Work data is created by cross tabulating a person’s main workplace address (Place of Work Data) with their place of usual residence to create a matrix of home to work.

The dataset is presented at the Statistical Local Area (SLA) level. SLAs are either whole LGAs or parts of LGAs and presenting the data at this level can show movements within the LGA for larger councils, as well as movement outside the LGA. This information is generally not available at the small area (suburb/locality) level due to geographic limitations when being coded or processed. Data are presented for both 2011 and 2006, but in some areas geographic boundary changes may render comparisons non-comparable. For this reason, while different years can be selected, numerical change is not shown. In some areas with stable statistical geography, comparison may be OK, but please check the boundaries being used.

Data source: Australian Bureau of Statistics, Journey to work data 2011 and 2006.

Local workers - Key statistics

This data summarises the demographic characteristics of people employed in the selected industry division (or all industries). Includes all persons working in the area regardless of where they live. Some of the figures in the summary table are taken from other topics. For those which don’t appear elsewhere, the following notes apply:

  • Persons – people aged 15 and over who were employed in the week prior to Census
  • Individual income – Median income is the midpoint of incomes for all employed people.

Data source: Australian Bureau of Statistics, Census of Population and Housing 2006 and 2011.

Local workers - Occupations

This data describes the occupations (by sex) of people employed in the selected industry. It includes all persons working in the local area regardless of where they live. Relates to the main job held in the week prior to Census. Data for occupations are coded using the Australian and New Zealand Standard Classification of Occupations (ANZSCO). The occupation classification is updated periodically to take account of emerging occupation groups and changes to the structure of the labour force.

Data are presented for the broad occupation groupings, which are broadly based on the education or skill level required to do a particular job

For more information please refer to the 2011 Census Dictionary, and the 2006 Australian and New Zealand Standard Classification of Occupations (ANZSCO).

Data source: Australian Bureau of Statistics, Census of Population and Housing 2006 and 2011.

Local workers - Qualifications

This data describes the level of the highest qualification (by sex) of employed persons in the selected industry. It includes all persons working in the local area regardless of where they live.

Qualifications are broken down by skill level, according to the Australian Standard Classification of Education (ASCED), (catalogue number 1272.0). Bachelor degree and higher level qualifications are generally provided by universities, while diploma level qualifications can be gained through universities or TAFE colleges. Certificate level qualifications are vocational based qualifications usually gained through TAFE and apprenticeships. Examples of particular occupations requiring certificate level qualifications are shown below:

  • With a Certificate I qualification, employment may be gained as:
    • a computer service technician;
    • a council worker (outdoors);
    • a dry cleaner;
    • a factory hand;
    • a florist;
    • a kitchenhand;
    • a polymer processor; and
    • a stablehand.
  • With a Certificate II qualification, employment may be gained as:
    • a bank officer;
    • a bushland regenerator;
    • a cleaner;
    • a farmer;
    • a film and video production technician;
    • a funeral attendant;
    • a hospitality operator;
    • a receptionist;
    • a sales assistant;
    • a screen printer
    • a shearer;
    • a tourist operator; and
    • a vehicle detailer.
  • With a Certificate III qualification, employment may be gained as:
    • an animal attendant;
    • a baker;
    • a beauty therapist;
    • a credit officer;
    • an electrician;
    • a homecare worker;
    • a milliner;
    • a motor mechanic;
    • a network administrator;
    • a painter and decorator;
    • a pastry cook;
    • a plumber;
    • a signwriter;
    • a sound technician;
    • a stonemason;
    • a tailor;
    • a tiler; and
    • a woodmachinist.
  • With a Certificate IV qualification, employment may be gained as:
    • an accounts clerk;
    • an architectural drafter;
    • a professional builder;
    • a community services worker;
    • a computer operator;
    • a fitness instructor;
    • a graphic designer;
    • an interior decorator;
    • a mechanical engineering technician;
    • a systems analyst; and
    • a visual merchandiser (please note this is now Diploma level, 2006)

For a complete listing of the occupations and qualifications available, please refer to the National Training Information Service.

For more information about Australian qualifications please refer to the Australian Qualifications Network.

Australian Bureau of Statistics, Census of Population and Housing 2006 and 2011.

Data source: Australian Bureau of Statistics, Census of Population and Housing 2006 and 2011.

Local workers - Field of qualifications

This dataset describes the field of study of the highest qualification completed of employed persons in the selected industry. The dataset includes all persons working in the local area regardless of where they live.

Qualifications are broken down by skill level, according to the Australian Standard Classification of Education (ASCED), (catalogue number 1272.0). Field of education is defined as the subject matter of an educational activity. Field of education is measured in terms of:

  • Theoretical content
  • Purpose of learning
  • Objects of interest
  • Methods and techniques
  • Tools and equipment

At the broad (1-digit) level, presented on the site, categories in field of study are distinguished from each other on the basis of the theoretical content of the course and the broad purpose for which the study is undertaken.

At the narrow (4-digit) level, presented on the site through drill-down, fields of study are distinguished from other narrow fields within the same broad field of study on the basis of the objects of interest and the purpose for which the study is undertaken.

Note that the field of qualification relates only to the highest qualification the person has received. For example, a person with a bachelor degree in engineering and a graduate diploma in education, would have only the education qualification recorded in the Census.

For a complete listing of the occupations and qualifications available, please refer to the training.gov.au.

For more information about Australian qualifications please refer to the Australian Qualifications Framework.

Data source: Australian Bureau of Statistics, Census of Population and Housing 2006 and 2011.

Local labour force - Key statistics

This dataset summarises the demographic characteristics of people in the local labour force. It includes people in the labour force who usually reside in the local area regardless of where they work (if working).

Some of the figures in the summary table are taken from other topics in the worker and labour force profiles sections of economy.id - please refer to the relevant data notes for those topics. For those which don’t appear elsewhere, the following notes apply:

  • Persons – persons in the labour force (persons aged 15 years and over who are looking for work, or are employed, full time, part-time or casually) who reside in the local area.
  • Individual income – low and high quartiles relate to those people earning in the lowest and highest 25% of incomes in the state respectively

Data source: Australian Bureau of Statistics, Census of Population and Housing 2011 and 2006

Local labour force - Industry

This dataset describes the industries (by sex) in which employed residents work. It applies only to people aged 15 and over who were employed in the week prior to Census and includes employed people who usually reside in the local area regardless of where they work.

Data for industry are coded using the Australia and New Zealand Standard Industrial Classification (ANZSIC). The industry classification is updated periodically to take account of emerging industries and changes in the structure of the economy.

This table presents information at the ANZSIC 1-digit (division) level, with sub-categories available at the 3-digit (group) level. A total of 293 industry categories are available at this level, by clicking on the table entries, or exporting the full version of the table. Only division level data appear in the charts.

The industry classification was last updated in 2006 (ANZSIC06).

For more information please refer to the 2006 Census Dictionary and the Australian and New Zealand Standard Industrial Classification, 2006.

Data source: Australian Bureau of Statistics, Census of Population and Housing 2011 and 2006.

Local labour force - Occupation

This data describes the occupations (by sex) in which employed residents work. It applies only to people aged 15 and over who were employed in the week prior to Census and includes employed people who usually reside in the local area regardless of where they work. Relates to the main job held in the week prior to Census.

Data for occupations are coded using the Australian and New Zealand Standard Classification of Occupations (ANZSCO). The occupation classification is updated periodically to take account of emerging occupation groups and changes to the structure of the labour force.

Data are presented for the broad occupation groupings. Occupations are ranked in descending order of the approximate level of skill or education required.

For more information please refer to the 2006 Census Dictionary, and the 2006 Australian and New Zealand Standard Classification of Occupations (ANZSCO).

Data source: Australian Bureau of Statistics, Census of Population and Housing 2011 and 2006.

Local labour force - Qualification

This dataset describes the level of the highest qualification (by sex) of persons in the local labour force. It includes people in the labour force who usually reside in the local area regardless of where they work (if working).

Qualifications are broken down by skill level, according to the Australian Standard Classification of Education (ASCED), (catalogue number 1272.0). Bachelor degree and higher level qualifications are generally provided by universities, while diploma level qualifications can be gained through universities or TAFE colleges. Certificate level qualifications are vocational based qualifications usually gained through TAFE and apprenticeships. Examples of particular occupations requiring certificate level qualifications are shown below:

  • With a Certificate I qualification, employment may be gained as:
    • a computer service technician;
    • a council worker (outdoors);
    • a dry cleaner;
    • a factory hand;
    • a florist;
    • a kitchenhand;
    • a polymer processor; and
    • a stablehand.
  • With a Certificate II qualification, employment may be gained as:
    • a bank officer;
    • a bushland regenerator;
    • a cleaner;
    • a farmer;
    • a film and video production technician;
    • a funeral attendant;
    • a hospitality operator;
    • a receptionist;
    • a sales assistant;
    • a screen printer
    • a shearer;
    • a tourist operator; and
    • a vehicle detailer.
  • With a Certificate III qualification, employment may be gained as:
    • an animal attendant;
    • a baker;
    • a beauty therapist;
    • a credit officer;
    • an electrician;
    • a homecare worker;
    • a milliner;
    • a motor mechanic;
    • a network administrator;
    • a painter and decorator;
    • a pastry cook;
    • a plumber;
    • a signwriter;
    • a sound technician;
    • a stonemason;
    • a tailor;
    • a tiler; and
    • a woodmachinist.
  • With a Certificate IV qualification, employment may be gained as:
    • an accounts clerk;
    • an architectural drafter;
    • a professional builder;
    • a community services worker;
    • a computer operator;
    • a fitness instructor;
    • a graphic designer;
    • an interior decorator;
    • a mechanical engineering technician;
    • a systems analyst; and
    • a visual merchandiser (please note this is now Diploma level, 2006)

For a complete listing of the occupations and qualifications available, please refer to training.gov.au.

For more information about Australian qualifications please refer to the Australian Qualifications Network.

Data source: Australian Bureau of Statistics, Census of Population and Housing 2011.

Local labour force - Field of qualification

This dataset describes the field of study of the highest qualification completed of employed persons in the selected industry. The dataset includes all persons living in the wider labour force region regardless of where they work. The labour region is defined empirically based on a reasonable commuting distance to the area of interest at Census time. More information is available in the labour region definition page.

Qualifications are broken down by skill level, according to the Australian Standard Classification of Education (ASCED), (catalogue number 1272.0) . Field of education is defined as the subject matter of an educational activity. Field of education is measured in terms of:

  • Theoretical content
  • Purpose of learning
  • Objects of interest
  • Methods and techniques
  • Tools and equipment

At the broad (1-digit) level, presented on the site, categories in field of study are distinguished from each other on the basis of the theoretical content of the course and the broad purpose for which the study is undertaken.

At the narrow (4-digit) level, presented on the site through drill-down, fields of study are distinguished from other narrow fields within the same broad field of study on the basis of the objects of interest and the purpose for which the study is undertaken.

Note that the field of qualification relates only to the highest qualification the person has received. For example, a person with a bachelor degree in engineering and a graduate diploma in education, would have only the education qualification recorded in the Census.

For a complete listing of the occupations and qualifications available, please refer to training.gov.au .

For more information about Australian qualifications please refer to the Australian Qualifications Network .

Data source: Australian Bureau of Statistics , Census of Population and Housing 2011 and 2006.

Local market - Key statistics

Age structure

Describes the age structure (by sex) of people who usually reside in the local area. Includes all persons except 'overseas visitors'.

Education institute attending

Describes the education institutions attended (by sex) by people who usually reside in the local area. Excludes 'overseas visitors'.

  • 'Catholic' refers to infant, primary and secondary schools run independently by the Catholic Church.
  • 'Independent' refers to private and other non-Government schools.
  • 'TAFE' refers to 'Technical and Further Education' institutions.
Proficiency in English

English proficiency aims to measure the ability of persons who speak ‘English as a Second Language’ to also speak English. The data, when viewed with other ethnic and cultural indicators, tends to reflect the ethnic composition of the population and the number of years of residence in Australia. In general, an area with a higher proportion of persons born in English-speaking countries or who emigrated from non-English speaking countries several decades ago is likely to have greater English-speaking proficiency.

Note: A person’s English proficiency is based on a subjective assessment and should therefore be treated with caution.

Responses to the question on Proficiency in English in the Census are subjective. For example, one respondent may consider that a response of 'Well' is appropriate if they can communicate well enough to do the shopping, while another respondent may consider such a response appropriate only for people who can hold a social conversation. Proficiency in English should be considered as an indicator of a person's ability to speak English and not a definitive measure of this ability.

Employment status (hours worked)

Describes the employment status (by sex) of people who usually reside in the local area. Excludes 'overseas vsitors'.

  • Includes persons aged 15 years and over.
  • 'Employed full time' is defined as having worked 35 hours or more in all jobs during the week prior to Census night. 'Unemployed' includes those not employed and actively looking for work, while 'Not in the labour force' includes all those people not employed and not looking for work, including retirees, students, home duties, discouraged jobseekers etc.
Qualifications

Describes the qualifications (by sex) of people who usually reside in the local area. Includes persons aged 15 years and over.

  • Excludes 'overseas visitors'.
  • Excludes schooling up to Year 12.

'No qualifications' refers to persons still studying for their first qualification, persons who do not have a qualification, and persons who have a qualification out of the scope of the Census version of the Census version of the Australian Standard Classification of Education (ASCED), 2001.

Household income

Describes the household income (by sex) of people who usually reside in the local area.

Household income comprises the total of incomes of all persons in the household who stated an income. Excludes ‘visitor only households’ and ‘other non classifiable households’.

  • 'Not stated' includes 'partial income not stated' and 'all incomes not stated'.
  • 'Partial income not stated' includes households where at least one, but not all, member(s) aged 15 years and over did not state an income and / or at least one household member aged 15 years and over was temporarily absent. In these cases, the aggregate of all stated individual incomes would be less than the true household income so these households are excluded from the classification.
  • 'All incomes not stated' includes households where no members present stated an income.
Housing tenure

Describes the housing tenure of occupied private dwellings in the local area. ‘Purchasing’ includes dwellings with a mortgage and those being purchased under a rent/buy scheme.

  • 'Renting' includes both public and private rental, and people renting from an employer. Other categories including rent-free occupancy and life tenure schemes are not shown in this summary.
Dwelling structure

Describes the dwelling structure of all occupied private dwellings in the local area. This data is classified by the Census collector on visiting the household, and the categories are broadly based on the density of the housing types.

  • 'Separate house' includes all free-standing dwellings separated from neighboring dwellings by a gap of at least half a metre.
  • 'Medium density' includes all semi-detached, row, terrace or townhouses and flats in a one or two storey block.
  • 'High density' includes all flats/apartments in a 3 or more storey block.

Data source: Australian Bureau of Statistics , Census of Population and Housing 2011.

Sources of income

Household Disposable income data is based on the National Institute for Economic and Industry Research micro-simulation modelling.

The base data source is the ABS Household Expenditure Survey (HES), (6535.0) conducted every 5 years. These are adjusted based on quarterly estimates of the relative composition of household types within the LGA derived from the ABS Labour Force Monthly Survey (and expenditure profiles of those household types in the HES).

The derived figures are updated by total LGA household disposable income derived from the other models, and updated quarterly based on changes in state level household consumption figures in the ABS State Accounts data.

Household Disposable income is an assessment of the average income available to each household, based on economic activity undertaken by the residents.

It should not be directly compared to Census data, and is usually considerably higher because:

  • Census data is collected in ranges, and underestimates the incomes at the top end of the scale, which are factored in to data derived from the Labour Force Survey and ATO.
  • Household Disposable income includes an estimate for the imputed value of ownership of dwellings, which forms part of the wealth of households but isn’t factored into their Census income.
  • Household Disposable income also includes superannuation payments which are often not included in Census stated income.
  • Over 10% of households in Census don’t state an income, and these incomes are included in the modelled data derived from the ATO and ABS Labour Force Survey data.

Household disposable income can, however be directly compared between areas and over time, which is presented on this site.

Sources used in the model:

  • ABS Household Expenditure Survey
  • ABS Labour Force Survey
  • ABS State Accounts
  • Census of Population and Housing

Household expenditure

The Household Expenditure Survey is run by the ABS every 5 years, and measures, by income level, the expenditure of households on various expenditure items. The NIEIR economic model adjusts the expenditure based on the economic and household characteristics of the local area to provide an estimate of local expenditure.

For more information, please see the ABS Household Expenditure Survey.

Please note that the calculation of net savings presented here is a broad indicator only. Disposable income includes components for the value of owned dwellings and also includes Superannuation which is forced saving. The measure is useful for comparing between geographic areas, but should not be taken as an exact measure of the amount of money the average household saves outside the superannuation system.

Economic impact model

Economic impact modelling is based on Input-Output tables, a component of the NIEIR microsimulation model derived from local differences between industries and Census journey to work data in the local economy. An input-output matrix describes how the different industries in an economy interrelate, and how supply chains operate in the local area. The microsimulation economic modelling reproduces the National Accounts data for local areas. Data sources in the model include:

  • Census Journey to Work data
  • ABS Labour Force Survey
  • Centrelink employment estimates
  • ABS building approvals – commercial floorspace estimates.
  • Dun & Bradstreet Business Startups
  • Australian Taxation Office worker income data
  • Microsimulation of known large employers.

The modelling produces a factor, which shows the flow-on effects of economic productivity in an industry sector, to other sectors and the total economy. The impact of local production on areas outside the local area is also modelled, based on Journey to Work information from the Census, updated for known more recent employment projects.

Please note that these results are theoretical only, and is meant to give a broad indication of the type of flow-on effects which may apply in the economy if certain industries are expanded or reduced. Where an industry currently has a very small number of jobs or output in the local economy, the results from this model should be treated with caution, as very little data is available. Where there is currently no employment or output in a particular industry, a result cannot be calculated.

While the model will accept any input, no checking is done to see how reasonable this input assumption is. It is also really intended only to model relatively minor changes in jobs and size of industries in the short term (less than 10% of total economy). Where economic impacts occur between industries it should not be assumed that any impact is immediate as it will take some time for the impact to be integrated into the existing economy.

As this is only a model of the real world, it is likely that real-world results would differ from what is shown in this table. .id and NIEIR take no responsibility for the use of this information.

Definitions

Direct impacts: represent the initial change in the industry selected. This refers to expenditure associated with the industry (e.g. labour, material, supplies, capital).

Indirect impacts (Industrial): The direct impacts from the initial expenditure creates additional activity in the local economy (‘ripple effect’. Indirect effects are the results of business-to-business transactions indirectly caused by the direct impacts.

Induced impacts (Consumption): An increase in revenue (from direct and indirect impacts) means that businesses increase wages and salaries by hiring more employees, increasing hours worked and raising wages. Households will then increase spending at local businesses.

Value of Agricultural Commodities produced

The Agricultural Census is run the the Australian Bureau of Statistics every 5 years, with the collection period normally co-inciding with the Census of Population and Housing, and the reference period being the previous financial year. The Agricultural Census covers all agricultural establishments with an Estimated Value of Agricultural Output (EVAO) of $50,000 or more in the reference year. Though it is a Census, there is usually less than 100% response, and some estimates are subject to sampling error.

Value of Agricultural Commodities data represent the gross value of production, derived from the Agricultural Census collection using estimates of production and average unit values of any given commodity in the marketplace over the reference year. Costs of production and marketing are not taken into account as these figures are gross values.

As well as the time series information shown for broad agricultural commodity groupings, further breakdown within each of these groups for the latest year only can be obtained by clicking on the names. Time series are not presented for this detailed information due to rapid changes in some agriculture sectors from year to year, and some changes to the classification of commodities between Agriculture Censuses.

Please note, that the ABS does not publish figures for some agricultural commodities in some areas, to protect the confidentiality of individual farming businesses. Where the table shows a "--" that figure has not been published, and is unavailable. Unpublished figures are included in totals and subtotals.

More information on this ABS collection can be obtained from:

Australian Bureau of Statistics, Value of Agricultural Commodities Produced, Australia, 2010-11. Cat. No. 7503.0

Event impact model

The event calculator works by estimating the impact a user defined level of spend has across a range of event related industries. The industries included in the calculator are those that research shows have the highest level of direct economic impact that can be attributed to the running of an event in the Shire of Moora. The estimated total spend of an event is broken down across the following industries based on the proportion of spend that can be attributed to each industry.

Industries included in the calculator:

  • Food Retailing
  • Other Retailing
  • Accommodation
  • Food and Beverage Services
  • Road Transport
  • Arts and Heritage
  • Sports and Recreation Activities

The proportion of spend allocated to each industry is dependent on the significance of the event, and they type of event which is determine by the user.

Event Significance

The significance of event is based on how far participants are prepared to travel to attend an event. An event can be classified into one of the following three significance levels.

  • Local - An event of local significance is assumed to attract attendance primarily from people who reside in the Shire of Moora and the neighbouring local government areas.
  • Region - An event of regional significance is assumed to attract attendance primarily from people who reside within 300-500 km of the location of the event.
  • State - an event of state significance is assumed to draw attendance from people across the state and the rest of Australia.

Event type

The event type is determined by the primary focus of the event. An event can be classified as one of two types of events, Arts and Heritage events (.e.g. music concert, market) or Sports and Recreation events (e.g. cycle race, fun run)

The Event Calculator has been designed primarily to give an indication of the potential impact of a small to medium size event that generates a total of between $25,000 and $250,000 of spend by the participants. Significant related costs that can be assumed would not occur within the Shire of Moora, such as domestic airfares, should not be included in the average daily spend figure. A small proportion of leakage of spend out of the local area is assumed in the calculation.

Location Quotient

The location quotient is a simple way of seeing which are the main industries in an area, relative to the wider region. LQ shows the percentage of the local economy characteristic (eg. employment, value add) in a particular industry divided by the percentage of the wider area (region, state, nation) that this industry makes up. It is derived as follows:

  • Local industry share = Industry value local area / Total Industries value local area
  • Benchmark industry share = Industry value benchmark area / Total Industries value benchmark area
  • LQ = Local industry share / Benchmark industry share

An LQ of exactly 1 means that industry is exactly as prevalent as in the benchmark region. An LQ above or below 1 highlights specialisations or lack thereof.

  • LQ < 0.8 - Indicates an industry which is more important in the benchmark region than the local area, and may represent an economic weakness or opportunity for growth.
  • 0.8 < LQ < 1.2 - Indicates the industry is broadly similar in importance in the local area compared to the benchmark region.
  • LQ > 1.2 - Indicates the industry is a significant specialisation in the local area – possibly a key economic strength. Higher numbers mean greater specialisations. Anything over 2 is a major specialisation.

LQs should be analysed in combination with the proportional economic share that industry represents. For example, an industry with an LQ of 2 reveals a specialisation but if that industry only represents 3% of the local economy, it may not be significant.

Value of tourism

The tourism and hospitality industries are estimated from the NIEIR microsimulation model by looking at the level of exports from specific industries which have a significant direct tourism and hospitality component. By measuring the level of export activity (i.e. goods and services purchased by individuals or business from outside the local area) for those industries that form part of a Tourism and hospitality cluster, the value of the tourism and hospitality industry can be estimated.

Of the 86 industries at the 2 digit ANZSIC code, 11 industries have a signification direct tourism output. There are also many other industries that contribute to tourism indirectly such as transport and education. The value of these industries to the economy is taken into account through the calculation of their indirect impact tourism spend flows through the local economy.

Using this methodology the total sum of all regional Tourism output comes to within 5% of the ABS Tourism Satellite account. Using a regional methodology such as this applied nationally reduces the likelihood of over estimating the impact of tourisms to local areas, as the sum of all regional tourism output cannot exceed the established national benchmark.

Direct Tourism industries
1 Digit Industry2 Digit Industry
Retail TradeMotor Vehicle and Motor Vehicle Parts Retailing
Retail Trade Fuel Retailing
Retail TradeFood Retailing
Retail TradeOther Store-Based Retailing
Retail TradeNon-Store Retailing and Retail Commission Based Buying
Accommodation and Food ServicesAccommodation
Accommodation and Food ServicesFood and Beverage Services
Arts and Recreation ServicesHeritage Activities
Arts and Recreation ServicesCreative and Performing Arts Activities
Arts and Recreation ServicesSports and Recreation Activities
Arts and Recreation ServicesGambling Activities

Source: NIEIR microsimulation tourism model

Other industries that contribute to tourism
Industry 2 Digit Industry
Rental, Hiring and Real Estate Services Residential property operators
Rail transport Rail transport
Road transport Taxi and other road transport
Road transport Road freight transport
Road transport Interurban and rural bus transport
Road transport Urban bus transport (including tramway)
Water Transport Water transport
Air and space transport Air and space transport
Other transport Scenic and Sightseeing Transport
Rental and Hiring Services (except Real Estate) Passenger car rental and hiring
Administrative and Support Services services Travel agency and tour arrangement
Education and training Preschool and school education
Education and training Tertiary education
Education and training Adult, community and other education

Source: ABS Tourism Satellite account

Shift-share analysis

Shift Share Analysis provides a useful mechanism for better interpreting changes in economic variables between different time periods. It is a way of breaking the growth or decline in an industry into three components to help understand what is driving the change. These three change components are commonly known as:

National/State growth effect (NS) - the amount of growth or decline in an industry that could be attributed to the overall growth of a larger area that encompasses the region's economy, usually state or national.

Industry mix effect (IM) - the amount of growth or decline in an industry that could be attributed to the performance of the specific industry at the national/state level

Regional competitive effect (RS) - the amount of growth or decline in a specific industry that could be attributed to a local advantage or disadvantage. This is generally the most interesting component as it clearly quantifies the level of advantage or disadvantage an industry has in the local area.

The three components for a time period Year 1 to Year 2 for a given local area within a larger benchmark area are simply derived as follows:

  • NS = Industry value local area (starting year) x Change in Total Economy value benchmark area (% change)
  • IM = Industry value local area (starting year) x Change in Industry value benchmark area (% change) – NS
  • RS = Industry value local area (ending year) – Industry value local area (starting year) – NS – IM

A positive regional competitive effect for an industry generally indicates the local industry is outperforming benchmark state/national trends (both overall economic trends and trends in that specific industry). A negative effect means that the industry is under performing compared to benchmark trends.

The sign (+/-) of a regional competitive effect does not necessarily match the sign of the net change in the variable being measured over the given time period. For example, a local area may have a positive net change in an industry value (output, value add, jobs) but record a negative regional competitive effect. This means that the industry is growing strongly at the national/state level, stronger than in the given local area, and this is then the main cause of the local industry growth.

Shift-share analysis needs to be combined with other local area data (e.g. population growth, building approvals) and specific area knowledge to ascertain what may have caused the area to grow above or below trend.

Tourism visitor summary

Tourism Research Australia conduct two major annual surveys for the purpose of promoting and understanding the Australian Tourism Market.

The International Visitor Survey (IVS) samples 40,000 short-term international travellers aged over 15 when they leave Australia. It contains approximately 100 questions and is interviewer-based. The primary purpose of this survey is to derive reliable estimates of visitors by country of origin, reason for visit and expenditure at the Tourism Region (TR) level. Results for smaller areas are available and shown here, but they are subject to sampling error.

Details of sampling errors and confidence intervals are found on the Tourism Research Australia International Visitor Survey Methodology page.

The National Visitor Survey (NVS) is conducted annually by telephone survey of approximately 120,000 Australian residents. It contains over 70 questions relating to travel within Australia by Australian residents, including destinations, purpose of trip, transportation, activities, expenditure and accommodation. This survey outputs data on overnight trips (including length of trip) and day trips by destination. Selected data from this survey are shown here. Details on the level of sampling error and further information on the methodology from the survey can be found the Tourism Research Australia National Visitor Survey Methodology page.

The results from each of these surveys are weighted by population and demographics to produce estimates of total visitation shown in this topic.

Results are produced by Tourism Research Australia from the IVS and NVS at the Tourism Region level, and at the SA2 level. SA2s do not always align to LGA boundaries, and in those cases, to derive the LGA level estimates shown in economy.id, a concordance has been used which apportions the SA2 to the LGA of interest based on an estimate of the total number of businesses on either side of a boundary. This is necessarily an approximation, but as these results are surveys based on respondents recollections of travel rather than absolute boundaries, it is not expected to have a major impact on the results for most LGAs.

Confidentiality and data reliability

To protect the confidentiality of individual respondents, and due to concerns about unreliable data due to small sample sizes, Tourism Research Australia requires the suppression of all data items from the IVS and NVS based on a sample size of less than 40. Though actual sample sizes are not shown on this site, this data suppression has been actioned. Data marked with a "-" have been suppressed because they are based on small and unreliable samples. In some cases, individual financial years' data have been suppressed for this reason, but a 5 year average may still be able to be published. This means that time series cannot be shown, but it still allows the user to gain an understanding of broad tourism patterns in the area.

Additional datasets may be available using different combinations of geography or categories, even where the data shown here has been suppressed. .id has access to the TRA Online database and we are happy to help our clients with custom data requests where they will help inform the tourism picture of the area. Please contact .id for more information.

Legal Statement

In addition to the above information, Tourism Research Australia legally require the following statement to be published with this dataset:

© Commonwealth of Australia 2016.

This work is copyright.  In addition to any use permitted under the Commonwealth Copyright Act 1968, the Commonwealth through Tourism Research Australia permits copies to be made in whole or in part for the purpose of promoting Australian tourism, provided that Tourism Research Australia (representing the Commonwealth) is identified on any copies as the author and the material is reproduced in its current form.  

Copies may not be made for a commercial purpose, that is, for sale, without the permission of Tourism Research Australia (representing the Commonwealth). The information in this data is presented in good faith and on the basis that neither the Commonwealth, nor its agents or employees, are liable (whether by reason of error, omission, negligence, lack of care or otherwise) to any person for any damage or loss whatsoever which has occurred or may occur in relation to that person taking or not taking (as the case may be) action in respect of any statement, information or advice given in this publication.

Data derived from Tourism Research Australia surveys are subject to sample error. Users of the data are advised to consult the sample error tables contained in Tourism Research Australia publications or otherwise available from Tourism Research Australia before drawing any conclusions or inferences, or taking any action, based on the data.

SA2s used in this report to build the LGA boundary for the tourism visitor pages are:

  • 509021241 - Moora

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