In 2023, the national per capita disposable personal income was ****** U.S. dollars. In the same year, the total per capita disposable personal income in the state of Connecticut was ****** U.S. dollars.

This dataset was utilized a join from enriched tables from ESRI which was curated from the 2020 Census from the United States Census Bureau and for city taxing districts polygon dataset are from 2024 published by the Idaho State Tax Commission. This layer has information for all cities within Idaho regarding the city population's Age, Sex and Race, Household Income, Disposable Income, Alcoholic Beverage Consumption, Total Population, Poverty Index, Employment, Housing, Total Population (2029), Home Value (2024), Housing Costs. For more information on how the data is curated for the Enrich tool please go the link below.

2024/2029 Esri Updated Demographics

In 2024, the average annual per capita disposable income of rural households in China was approximately ****** yuan, roughly ** percent of the income of urban households. Although living standards in China’s rural areas have improved significantly over the past 20 years, the income gap between rural and urban households is still large. Income increase of China’s households From 2000 to 2020, disposable income per capita in China increased by around *** percent. The fast-growing economy has inevitably led to the rapid income increase. Furthermore, inflation has been maintained at a lower rate in recent years compared to other countries. While the number of millionaires in China has increased, many of its population are still living in humble conditions. Consequently, the significant wealth gap between China’s rich and poor has become a social problem across the country. However, in recent years rural areas have been catching up and disposable income has been growing faster than in the cities. This development is also reflected in the Gini coefficient for China, which has decreased since 2008. Urbanization in China The urban population in China surpassed its rural population for the first time in 2011. In fact, the share of the population residing in urban areas is continuing to increase. This is not surprising considering remote, rural areas are among the poorest areas in China. Currently, poverty alleviation has been prioritized by the Chinese government. The measures that the government has taken are related to relocation and job placement. With the transformation and expansion of cities to accommodate the influx of city dwellers, neighboring rural areas are required for the development of infrastructure. Accordingly, land acquisition by the government has resulted in monetary gain by some rural households.

Disposable Income per Capita: Urban: Guangdong: Shenzhen data was reported at 76,910.000 RMB in 2023. This records an increase from the previous number of 72,718.228 RMB for 2022. Disposable Income per Capita: Urban: Guangdong: Shenzhen data is updated yearly, averaging 25,438.260 RMB from Dec 1988 (Median) to 2023, with 36 observations. The data reached an all-time high of 76,910.000 RMB in 2023 and a record low of 2,569.200 RMB in 1988. Disposable Income per Capita: Urban: Guangdong: Shenzhen data remains active status in CEIC and is reported by Shenzhen Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HF: Disposable Income per Capita: Prefecture Level City: Urban.

Annual adjusted household disposable income including social transfers in kind.

In this file there are statistics for a number of variables broken down by Malmö’s different areas over time. Source Unless otherwise stated, the statistics in this database are retrieved from Statistics Sweden’s (SCB) regional database, Skånedatabasen or from Statistics Sweden’s area statistics database (OSDB). The Skåne database and OSDB show data from several different sources that Statistics Sweden has compiled on a geographical level. The statistics only cover persons who are part of the population registered in the population. Therefore, persons without a residence permit, such as asylum seekers, and persons who simply have not registered in the municipality are not included. Statistics Sweden does not provide statistics on which language residents speak, which religion you belong to or what ethnicity or political views you have. Therefore, such data is not available here either. However, the Electoral Authority reports election results per constituency on its website val.se. There are statistics from the last election as well as several previous elections available. Please note, however, that the constituencies do not necessarily follow the division of the city made here. Update The data is updated every spring as Statistics Sweden releases the figures to the municipality. Most variables are available for the year before. However, income and employment data are released with another year’s backlog. Unless otherwise stated, the date of measurement is 31 December of each year. Geographical breakdown Unless otherwise stated, the data is available for Malmö as a whole and broken down into urban areas (5 pieces), districts (10 pieces) and subareas (136 pieces). In addition to these, there is a residual post that contains the people who are not written in a specific place in the municipality, have protected identity and more. These people are also part of the total. In several of the subareas there are no or only a few registered population registers. Therefore, no data are reported for these areas. Examples of such sub-areas are parks such as Pildammsparken and Kroksbäcksparken and industrial areas such as Fosieby Industriområde and Spillepengen. Privacy clearance In order to protect the identity of individuals, the data is confidentially audited. This means that small values are suppressed, i.e. replaced by empty cells. However, the values are included in summaries. In general, the following rules apply: * No statistics are reported for geographical areas with very few housing. * No cells with fewer than 5 individuals are reported. For data classified as sensitive (e.g. income and country of birth), larger values can also be suppressed. * In cases where a subcategory (e.g. a training category) is too small to be accounted for, all categories are often suppressed. Please use the numbers, but use “City Office, Malmö City” as the source.

Disposable Income per Capita: Urban: Yunnan: Kunming data was reported at 57,444.000 RMB in 2024. This records an increase from the previous number of 55,501.000 RMB for 2023. Disposable Income per Capita: Urban: Yunnan: Kunming data is updated yearly, averaging 30,016.187 RMB from Dec 2003 (Median) to 2024, with 22 observations. The data reached an all-time high of 57,444.000 RMB in 2024 and a record low of 7,979.000 RMB in 2003. Disposable Income per Capita: Urban: Yunnan: Kunming data remains active status in CEIC and is reported by Kunming Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HF: Disposable Income per Capita: Prefecture Level City: Urban.

In India, the share of the population that earned at least the equivalent of the highest 10 percent of global income earners as of 2022 in purchasing power parity (PPP) terms was *** percent. Hyderabad topped the list with the highest share of the upper or high-class category consumers, at over ** percent. Cities from south India topped the list with the first four ranks, followed by the national capital, Delhi.

This dataset provides statistics on disposable income and primary income, for large regions (TL2) and small regions (TL3) when available.

Data source and definition

Income here is measured from the macro perspective produced by the regional accounts. Income data is collected from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. In order to allow comparability over time and across countries, income in current prices are transformed into constant prices and PPP measures (link). For the income series, the deflator retained is the 'implicit national price index of households final consumption expenditure', which is the deflator used in SNA for the transaction P31S14.

Definition of regions

Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).

Use of economic data on small regions

When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting, see the list of OECD metropolitan regions (xlsx) and the EU methodology (link).

Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).

Cite this dataset

OECD Regions and Cities databases http://oe.cd/geostats

Further information

• The interactive web-tool OECD Regions and Cities Statistical Atlas
• The report OECD Regions and Cities at a Glance

Contact: RegionStat@oecd.org

Disposable Personal Income in India increased to 296383300 INR Million in 2023 from 273364818.90 INR Million in 2022. This dataset provides - India Total Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset was utilized a join from enriched tables from ESRI which was curated from the 2020 Census from the United States Census Bureau and for city taxing districts polygon dataset are from 2024 published by the Idaho State Tax Commission. This layer has information for all cities within Idaho regarding the city population's Age, Sex and Race, Household Income, Disposable Income, Alcoholic Beverage Consumption, Total Population, Poverty Index, Employment, Housing, Total Population (2029), Home Value (2024), Housing Costs. For more information on how the data is curated for the Enrich tool please go the link below.

2024/2029 Esri Updated Demographics

Content

A dataset of counties that are representative for Germany with regard to

the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.

In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.

This dataset was utilized a join from enriched tables from ESRI which was curated from the 2020 Census from the United States Census Bureau and for city taxing districts polygon dataset are from 2024 published by the Idaho State Tax Commission. This layer has information for all cities within Idaho regarding the city population's Age, Sex and Race, Household Income, Disposable Income, Alcoholic Beverage Consumption, Total Population, Poverty Index, Employment, Housing, Total Population (2029), Home Value (2024), Housing Costs. For more information on how the data is curated for the Enrich tool please go the link below.

2024/2029 Esri Updated Demographics

Market Overview The global evening economy market experienced a significant decline due to the COVID-19 pandemic, but is expected to rebound strongly in the coming years. The market is projected to grow from USD XXX million in 2025 to USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period. The increasing urbanization, rising disposable income, and growing preference for nightlife and entertainment are the key drivers of the market growth. The market is segmented into four major types: eating and drinking economy, entertainment economy, nightlife economy, and others. The eating and drinking economy segment holds the largest market share due to the increasing popularity of fine dining, casual dining, and fast food restaurants. Regional Trends The Asia Pacific region is expected to dominate the evening economy market throughout the forecast period. The region is home to some of the world's largest and most vibrant cities, such as Tokyo, Shanghai, and Seoul. These cities offer a wide range of evening entertainment options, from live music and theater to nightclubs and bars. North America and Europe are also major markets for the evening economy, with cities such as New York City, London, and Paris attracting millions of visitors each year. The Middle East and Africa region is expected to witness the fastest growth in the coming years, driven by the increasing disposable income and the growing number of young people in the region.

This dataset was utilized a join from enriched tables from ESRI which was curated from the 2020 Census from the United States Census Bureau and for city taxing districts polygon dataset are from 2024 published by the Idaho State Tax Commission. This layer has information for all cities within Idaho regarding the city population's Age, Sex and Race, Household Income, Disposable Income, Alcoholic Beverage Consumption, Total Population, Poverty Index, Employment, Housing, Total Population (2029), Home Value (2024), Housing Costs. For more information on how the data is curated for the Enrich tool please go the link below.

2024/2029 Esri Updated Demographics

This statistic displays the disposable income in the Netherlands in 2013, by residence location (in euros). That year on average in the Netherlands, the average disposable income was ****** euros. The average disposable income was the highest in small villages nearby cities, with over ****** euros. On the other hand, in large villages in remote locations, the average disposable income was only ****** euros.

EIU’s CityData contains pricing information on over 160 products and services in 140 cities worldwide, gathered from the EIU Worldwide Cost of Living Survey. More than 50,000 individual prices are collected by field correspondents in each survey. Prices are given for various stores: supermarkets, mid-priced stores, and higher-priced specialty outlets. Prices cover: National economic indicators; Food and drink; Household supplies; Personal care; Tobacco; Clothing; Utilities; Domestic help; Recreation; Transport; Office and residential rents; Schools, health and sports; Business trip costs; Salaries and disposable incomes. Prices correspond to the price the customer is charged, not recommended retail prices or manufacturers’ costs. Use CityData to support your market entry strategy, assess international pricing for a specific product(s), analyze historical pricing patterns for goods and services since 1990, compare the cost of doing business worldwide, and perform city-to-city pricing comparisons. EIU CityData provides the most complete picture of global price levels. More information is available at EIU CityData Information.

Modular Walk-In Closet System Market Outlook

According to our latest research, the global modular walk-in closet system market size reached USD 7.92 billion in 2024, reflecting the growing demand for customizable storage solutions in both residential and commercial spaces. The market is experiencing a robust growth trajectory, with a compound annual growth rate (CAGR) of 7.1% projected from 2025 to 2033. By the end of 2033, the global modular walk-in closet system market is forecasted to achieve a valuation of USD 14.95 billion. This impressive growth is primarily driven by increasing urbanization, rising disposable incomes, and the evolving preferences for personalized home organization systems. As per our latest research, the marketÂ’s expansion is underpinned by a surge in renovation activities and a heightened focus on maximizing space efficiency in modern living environments.

One of the most significant growth factors propelling the modular walk-in closet system market is the rising trend of urbanization and the accompanying reduction in living space, especially in metropolitan areas. As cities become more densely populated, homeowners and renters alike are seeking innovative solutions to optimize their available space. Modular walk-in closet systems, with their flexibility and adaptability, offer an ideal solution for maximizing storage without compromising on aesthetics or functionality. The ability to customize these systems according to individual needs—from shelving and hanging space to integrated drawers and accessory organizers—has resonated strongly with consumers. This trend is further amplified by the proliferation of home improvement and interior design content on digital platforms, inspiring consumers to invest in sophisticated storage solutions that enhance both organization and visual appeal.

Another key driver for the modular walk-in closet system market is the significant increase in disposable income and changing lifestyle preferences, particularly in emerging economies. As consumers become more affluent, there is a marked shift towards premiumization in home furnishings and fixtures. The demand for high-quality, durable, and aesthetically pleasing closet systems has soared, with many consumers willing to invest in modular solutions that offer long-term value. Additionally, the growing influence of real estate trends, such as open-plan living and luxury apartments, has further fueled the adoption of modular walk-in closet systems. Developers and interior designers are increasingly incorporating these systems into new residential and commercial projects, recognizing their ability to enhance property value and appeal to discerning buyers.

Technological advancements and innovation in materials have also played a pivotal role in the marketÂ’s growth. Manufacturers are leveraging cutting-edge design software and precision engineering to create modular walk-in closet systems that are not only highly functional but also customizable to an unprecedented degree. The integration of smart features, such as automated lighting, climate control, and IoT-enabled inventory management, is gaining traction, particularly among tech-savvy consumers. Additionally, the use of sustainable materials and eco-friendly manufacturing processes is becoming a major selling point, as environmental consciousness continues to shape consumer purchasing decisions. These technological and material innovations are enabling manufacturers to cater to a broader spectrum of customer preferences, further expanding the marketÂ’s reach.

Regionally, North America continues to dominate the modular walk-in closet system market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The robust demand in North America can be attributed to high disposable incomes, a strong culture of homeownership, and a well-established home improvement industry. Europe is witnessing steady growth, driven by the increasing adoption of modern living concepts and a focus on sustainable home solutions. Meanwhile, the Asia Pacific region is emerging as a lucrative market, fueled by rapid urbanization, rising middle-class populations, and a burgeoning real estate sector. Latin America and the Middle East & Africa are also showing promising growth potential, supported by increasing investments in residential and commercial infrastructure.

In the realm of modular walk-in closet systems, the inclusion of an <a

China Home Loan Market size was valued at USD 37.8 Trillion in 2024 and is projected to reach USD 59 Trillion by 2032, growing at a CAGR of 5.7 % from 2026 to 2032. The China home loan market is primarily driven by rapid urbanization, rising disposable incomes, and supportive government policies. As more people migrate to cities, the demand for housing increases, leading to a surge in mortgage financing. Government initiatives, such as reduced down payments and lower mortgage rates, have made homeownership more accessible, further fueling market growth.​ Additionally, the digitalization of mortgage services has streamlined the loan approval process, enhancing customer experience and attracting more borrowers. The growing middle class, with higher income levels, is increasingly investing in property, contributing to the expansion of the home loan market. These factors collectively create a robust environment for the continued growth of China's home loan sector.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.