In 2023, the real median household income for householders aged 15 to 24 was at 54,930 U.S. dollars. The highest median household income was found amongst those aged between 45 and 54. Household median income for the United States since 1990 can be accessed here.

Graph and download economic data for Unemployment Rate - 20 Yrs. & over (LNS14000024) from Jan 1948 to Feb 2025 about 20 years +, household survey, unemployment, rate, and USA.

In 2023, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

Graph and download economic data for Labor Force Participation Rate - 16-19 Yrs. (LNS11300012) from Jan 1948 to Feb 2025 about 16 to 19 years, participation, labor force, labor, household survey, rate, and USA.

Russia Purchasing Capacity: Avg Household Income per Capita: Payment: Gas Supply data was reported at 99.500 Prev Year=100 in 2018. This records an increase from the previous number of 96.700 Prev Year=100 for 2017. Russia Purchasing Capacity: Avg Household Income per Capita: Payment: Gas Supply data is updated yearly, averaging 99.200 Prev Year=100 from Dec 1995 (Median) to 2018, with 24 observations. The data reached an all-time high of 116.300 Prev Year=100 in 1999 and a record low of 24.800 Prev Year=100 in 1995. Russia Purchasing Capacity: Avg Household Income per Capita: Payment: Gas Supply data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HD002: Purchasing Capacity: Average Household Income per Capita: Annual.

Household Expenditure per Capita: Avg per Month: FE: Kamchatka Territory data was reported at 53,381.000 RUB in 2023. This records an increase from the previous number of 43,991.000 RUB for 2022. Household Expenditure per Capita: Avg per Month: FE: Kamchatka Territory data is updated yearly, averaging 16,928.500 RUB from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 53,381.000 RUB in 2023 and a record low of 2,263.000 RUB in 2000. Household Expenditure per Capita: Avg per Month: FE: Kamchatka Territory data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA020: Household Expenditure per Capita: Annual: by Region.

In 2024, the average annual per capita disposable income of households in China amounted to approximately 41,300 yuan. Annual per capita income in Chinese saw a significant rise over the last decades and is still rising at a high pace. During the last ten years, per capita disposable income roughly doubled in China. Income distribution in China As an emerging economy, China faces a large number of development challenges, one of the most pressing issues being income inequality. The income gap between rural and urban areas has been stirring social unrest in China and poses a serious threat to the dogma of a “harmonious society” proclaimed by the communist party. In contrast to the disposable income of urban households, which reached around 54,200 yuan in 2024, that of rural households only amounted to around 23,100 yuan. Coinciding with the urban-rural income gap, income disparities between coastal and western regions in China have become apparent. As of 2023, households in Shanghai and Beijing displayed the highest average annual income of around 84,800 and 81,900 yuan respectively, followed by Zhejiang province with 63,800 yuan. Gansu, a province located in the West of China, had the lowest average annual per capita household income in China with merely 25,000 yuan. Income inequality in China The Gini coefficient is the most commonly used measure of income inequality. For China, the official Gini coefficient also indicates the astonishing inequality of income distribution in the country. Although the Gini coefficient has dropped from its high in 2008 at 49.1 points, it still ranged at a score of 46.5 points in 2023. The United Nations have set an index value of 40 as a warning level for serious inequality in a society.

This publication covers annual estimates for waste collected by local authorities in England and the regions. These statistics are based on data submitted by all local authorities in England to WasteDataFlow on the waste they collect and manage.

The methodology and recycling explainer documents give background and context to this statistical notice, accompanying datasets and the waste and recycling measures they present.

There is also a further historical note on the definition of local authority collected waste relating to earlier releases.

The entire raw dataset is available in CSV format and can be found here: https://www.data.gov.uk/dataset/0e0c12d8-24f6-461f-b4bc-f6d6a5bf2de5/wastedataflow-local-authority-waste-management" class="govuk-link">WasteDataFlow - Local Authority waste management - data.gov.uk

Historic releases

https://webarchive.nationalarchives.gov.uk/ukgwa/20250102235615/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2022-2023

https://webarchive.nationalarchives.gov.uk/ukgwa/20230802024231/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results-202122" class="govuk-link">2021- 2022

https://webarchive.nationalarchives.gov.uk/ukgwa/20220503105415/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2020 - 2021

https://webarchive.nationalarchives.gov.uk/ukgwa/20210728220801/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2019-2020

https://webarchive.nationalarchives.gov.uk/ukgwa/20200604042448/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2018 - 2019

https://webarchive.nationalarchives.gov.uk/ukgwa/20190903035029/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2017 - 2018

https://webarchive.nationalarchives.gov.uk/ukgwa/20181207030346/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2016 - 2017

https://webarchive.nationalarchives.gov.uk/ukgwa/20170418015547/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2015 - 2016 This includes the ad hoc release entitled “Provisional 2016/17 local authority data on waste collection and treatment for England (April to June and July to September 2016)”.

https://webarchive.nationalarchives.gov.uk/ukgwa/20160512131028/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2014 - 2015

https://webarchive.nationalarchives.gov.uk/ukgwa/20150401112814/https://www.gov.uk/government/statistics/local-authority-collected-waste-management-annual-results" class="govuk-link">2013 - 2014

https://webarchive.nationalarchives.gov.uk/ukgwa/20140321171631/https://www.gov.uk/government/publications/local-authority-collected-waste-management-annual-results" class="govuk-link">2012 - 2013

Historic datasets

Historic datasets

Household Expenditure per Capita: Avg per Month: NW: Republic of Komi data was reported at 35,674.000 RUB in 2023. This records an increase from the previous number of 28,634.000 RUB for 2022. Household Expenditure per Capita: Avg per Month: NW: Republic of Komi data is updated yearly, averaging 17,026.500 RUB from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 35,674.000 RUB in 2023 and a record low of 1,840.000 RUB in 2000. Household Expenditure per Capita: Avg per Month: NW: Republic of Komi data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA020: Household Expenditure per Capita: Annual: by Region.

Household Expenditure per Capita: Avg per Month: CF: Ivanovo Region data was reported at 31,344.000 RUB in 2023. This records an increase from the previous number of 26,565.000 RUB for 2022. Household Expenditure per Capita: Avg per Month: CF: Ivanovo Region data is updated yearly, averaging 10,774.500 RUB from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 31,344.000 RUB in 2023 and a record low of 759.000 RUB in 2000. Household Expenditure per Capita: Avg per Month: CF: Ivanovo Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA020: Household Expenditure per Capita: Annual: by Region.

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

Abstract

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm. These microdata files present detailed expenditure and income data for the Diary component of the CE for 2002. They include weekly expenditure (EXPD) and annual income (DTBD) files. The data in EXPD and DTBD files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. Estimates of average expenditures in 2002 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2002. A list of recent publications containing data from the CE appears at the end of this documentation. The microdata files are in the public domain and with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2002".

Analysis unit

Consumer Units

Kind of data

Sample survey data [ssd]

Sampling procedure

Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons. The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2002 sample is composed of 105 areas. The design classifies the PSUs into four categories: • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

The sampling frame (that is, the list from which housing units were chosen) for the 2002 survey is generated from the 1990 Population Census 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (ED's) from the Census that fail to meet the criterion for good addresses for new construction, and all ED's in nonpermit-issuing areas are grouped into the area segment frame. To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year. During the last 6 weeks of the year, however, the Diary Survey sample is supplemented to twice its normal size to increase the reporting of types of expenditures unique to the holidays.

STATE IDENTIFIER Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data. To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

INTERPRETING THE DATA Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially. Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs. CUs with members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

Mode of data collection

Computer Assisted Personal Interview [capi]

About this dataset

Context

The dataset tabulates the Carbondale household income by age. The dataset can be utilized to understand the age-based income distribution of Carbondale income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Carbondale, PA annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Carbondale, PA household incomes: Comparative analysis across 16 income brackets

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Carbondale income distribution by age. You can refer the same here

This statistic shows the mean disposable household income in the United States in 2023, by age. In 2023, the disposable income of a household led by a person between the ages of 35 and 44 years old was 109,075 U.S. dollars per year.

Household Expenditure per Capita: Avg per Month: CF: Orel Region data was reported at 30,640.000 RUB in 2023. This records an increase from the previous number of 27,022.000 RUB for 2022. Household Expenditure per Capita: Avg per Month: CF: Orel Region data is updated yearly, averaging 11,008.500 RUB from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 30,640.000 RUB in 2023 and a record low of 1,098.000 RUB in 2000. Household Expenditure per Capita: Avg per Month: CF: Orel Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA020: Household Expenditure per Capita: Annual: by Region.

In 2023, the highest average amount of disposable income for any age group occurred in the 35 to 44-year-old group, while the age group with the lowest average disposable income were those aged 85 and over.

Quarterly current and capital accounts for the household sector, including property income, disposable income, net saving and net lending, Canada.