About this dataset

Context

The dataset presents the median household income across different racial categories in Au Gres township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Au Gres township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 98.70% of the total residents in Au Gres township. Notably, the median household income for White households is $53,539. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $53,539.

https://i.neilsberg.com/ch/au-gres-township-mi-median-household-income-by-race.jpeg" alt="Au Gres township median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Gres township.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Gres township median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Au Sable charter township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Au Sable charter township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 94.09% of the total residents in Au Sable charter township. Notably, the median household income for White households is $46,614. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $46,614.

https://i.neilsberg.com/ch/au-sable-charter-township-mi-median-household-income-by-race.jpeg" alt="Au Sable charter township median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Sable charter township.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Sable charter township median household income by race. You can refer the same here

The Gross Domestic Product per capita in Australia was last recorded at 61211.90 US dollars in 2024. The GDP per Capita in Australia is equivalent to 485 percent of the world's average. This dataset provides - Australia GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Au Gres Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Au Gres township did not include 3, 5, 6, or 7-person households. Across the different household sizes in Au Gres township the mean income is $64,189, and the standard deviation is $20,953. The coefficient of variation (CV) is 32.64%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $41,661. It then further increased to $83,095 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/au-gres-township-mi-median-household-income-by-household-size.jpeg" alt="Au Gres Township, Michigan median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Gres township median household income. You can refer the same here

In 2023, Switzerland led the ranking of countries with the highest average wealth per adult, with approximately ******* U.S. dollars per person. Luxembourg was ranked second with an average wealth of around ******* U.S. dollars per adult, followed by Hong Kong SAR. However, the figures do not show the actual distribution of wealth. The Gini index shows wealth disparities in countries worldwide. Does wealth guarantee a longer life? As the old adage goes, “money can’t buy you happiness”, yet wealth and income are continuously correlated to the quality of life of individuals in different countries around the world. While greater levels of wealth may not guarantee a higher quality of life, it certainly increases an individual’s chances of having a longer one. Although they do not show the whole picture, life expectancy at birth is higher in the wealthier world regions. Does money bring happiness? A number of the world’s happiest nations also feature in the list of those countries for which average income was highest. Finland, however, which was the happiest country worldwide in 2022, is missing from the list of the top twenty countries with the highest wealth per adult. As such, the explanation for this may be the fact that the larger proportion of the population has access to a high income relative to global levels. Measures of quality of life Criticism of the use of income or wealth as a proxy for quality of life led to the creation of the United Nations’ Human Development Index. Although income is included within the index, it also has other factors taken into account, such as health and education. As such, the countries with the highest human development index can be correlated to those with the highest income levels. That said, none of the above measures seek to assess the physical and mental environmental impact of a high quality of life sourced through high incomes. The happy planet index demonstrates that the inclusion of experienced well-being and ecological footprint in place of income and other proxies for quality of life results in many of the world’s materially poorer nations being included in the happiest.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Au Train township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Au Train township, the median household income for the households where the householder is White increased by $14,977(28.63%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $52,315 in 2013 and $67,292 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Au Train township, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Train township.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Train township median household income by race. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Au Train Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Au Train township did not include 3, 5, 6, or 7-person households. Across the different household sizes in Au Train township the mean income is $63,246, and the standard deviation is $43,009. The coefficient of variation (CV) is 68%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $18,615. It then further increased to $104,424 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/au-train-township-mi-median-household-income-by-household-size.jpeg" alt="Au Train Township, Michigan median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Train township median household income. You can refer the same here

The Gross Domestic Product per capita in Australia was last recorded at 60082.01 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in Australia, when adjusted by Purchasing Power Parity is equivalent to 338 percent of the world's average. This dataset provides - Australia GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The house price-to-income ratio in Australia was ***** as of the fourth quarter of 2024. This ratio, calculated by dividing nominal house prices by nominal disposable income per head, increased from the previous quarter. The price-to-income ratio can be used to measure housing affordability in a specific area. Australia's property bubble There has been considerable debate over the past decade about whether Australia is in a property bubble or not. A property bubble refers to a sharp increase in the price of property that is disproportional to income and rental prices, followed by a decline. In Australia, rising house prices have undoubtedly been an issue for many potential homeowners, pricing them out of the market. Along with the average house price, high mortgage interest rates have exacerbated the issue. Is the homeownership dream out of reach? Housing affordability has varied across the different states and territories in Australia. In 2024, the median value of residential houses was the highest in Sydney compared to other major Australian cities, with Brisbane becoming an increasingly expensive city. Nonetheless, expected interest rate cuts in 2025, alongside the expansion of initiatives to improve Australia's dwelling stock, social housing supply, and first-time buyer accessibility to properties, may start to improve the situation. These encompass initiatives such as the Australian government's Help to Buy scheme and the Housing Australia Future Fund Facility (HAFFF) and National Housing Accord Facility (NHAF) programs.

The Gross Domestic Product per capita in Japan was last recorded at 37144.91 US dollars in 2024. The GDP per Capita in Japan is equivalent to 294 percent of the world's average. This dataset provides - Japan GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

LGA based data for Selected Medians and Averages, in Place of Enumeration Profile (PEP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s …Show full descriptionLGA based data for Selected Medians and Averages, in Place of Enumeration Profile (PEP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, a family’s income, total household income, mortgage repayment, rental payments, number of persons per bedroom and household size. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

This dataset presents the Rental Affordability Index (RAI) for all dwellings. The data uses different income values for each region within the Greater Capital Cities, and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory does not form part of this dataset. National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually. It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income: RAI = (Median Income ∕ Qualifying Income) x 100 In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress. For more information on the Rental Affordability Index please refer to SGS Economics and Planning. The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia. AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Au Sable Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, only 1, and 2-person households were found in Au Sable township. Across the different household sizes in Au Sable township the mean income is $43,236, and the standard deviation is $28,663. The coefficient of variation (CV) is 66.29%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $22,969. It then further increased to $63,504 for 2-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/au-sable-township-mi-median-household-income-by-household-size.jpeg" alt="Au Sable Township, Michigan median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Sable township median household income. You can refer the same here

SA1 based data for Selected Medians and Averages, in General Community Profile (GCP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s …Show full descriptionSA1 based data for Selected Medians and Averages, in General Community Profile (GCP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, a family’s income, total household income, mortgage repayment, rental payments, number of persons per bedroom and household size. The data is by SA1 2016 boundaries. Periodicity: 5-Yearly. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

GCCSA based data for Selected Medians and Averages, in Place of Enumeration Profile (PEP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s …Show full descriptionGCCSA based data for Selected Medians and Averages, in Place of Enumeration Profile (PEP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, a family’s income, total household income, mortgage repayment, rental payments, number of persons per bedroom and household size. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

GCCSA based data for Selected Medians and Averages, for 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, total household income, …Show full descriptionGCCSA based data for Selected Medians and Averages, for 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, total household income, mortgage repayment, rental payments, number of persons per bedroom, household size and proportion of dwellings in need of one or more extra bedrooms. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

GCCSA based data for Selected Medians and Averages, in General Community Profile (GCP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s …Show full descriptionGCCSA based data for Selected Medians and Averages, in General Community Profile (GCP), 2016 Census. The median or average was calculated in the following categories: a person’s age, a person’s income, a family’s income, total household income, mortgage repayment, rental payments, number of persons per bedroom and household size. The data is by GCCSA 2016 boundaries. Periodicity: 5-Yearly. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

This dataset presents the Rental Affordability Index (RAI) for 3 bedroom dwellings. The data uses different income values for each region within the Greater Capital Cities, and spans the quarters Q1 2011 to Q2 2021. The RAI covers all states with available data, the Northern Territory and Western Australia does not form part of this dataset. National Shelter, Bendigo Bank, The Brotherhood of St Laurence, and SGS Economics and Planning have released the RentalAffordability Index (RAI) on a biannual basis since 2015. Since 2019, the RAI has been released annually. It is generally accepted that if housing costs exceed 30% of a low-income household's gross income, the household is experiencing housing stress (30/40 rule). That is, housing is unaffordable and housing costs consume a disproportionately high amount of household income. The RAI uses the 30 per cent of income rule. Rental affordability is calculated using the following equation, where 'qualifying income' refers to the household income required to pay rent where rent is equal to 30% of income: RAI = (Median income ∕ Qualifying Income) x 100 In the RAI, households who are paying 30% of income on rent have a score of 100, indicating that these households are at the critical threshold for housing stress. A score of 100 or less indicates that households would pay more than 30% of income to access a rental dwelling, meaning they are at risk of experiencing housing stress. For more information on the Rental Affordability Index please refer to SGS Economics and Planning. The RAI is a price index for housing rental markets. It is a clear and concise indicator of rental affordability relative to household incomes, applied to geographic areas across Australia. AURIN has spatially enabled the original data using geometries provided by SGS Economics and Planning. Values of 'NA' in the original data have been set to NULL.

Australia Toys And Games Market size was valued at USD 3.45 Billion in 2024 and is projected to reach USD 4.82 Billion by 2032, growing at a CAGR of 4.3% from 2025 to 2032.

Australia Toys And Games Market Dynamics

The key market dynamics that are shaping the Australia toys and games market include:

Key Market Drivers

Increase in Disposable Income and Consumer Spending: As the Australian economy has been steadily recovering, rising disposable income has led to higher consumer spending, especially in the children’s toy and gaming sectors. According to the Australian Bureau of Statistics, household disposable income per capita increased by 3.5% in 2021, which directly contributed to greater expenditure on children's entertainment and educational toys. This boost in income is helping families allocate more for premium toys and games, expanding the market.

Growth of Online Retail and E-commerce: The shift towards online shopping has been a major driver for the toys and games market in Australia.