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Context
The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.
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).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here
The statistic shows the average number of residents living in India's households in 2012, by state and union territory. In that year, Punjab and Arunachal Pradesh had an average of five people living in a household, while the lowest average size was in Tamil Nadu with 3.9 people per household.
In the financial year 2021, the average annual expenditure of rich households in India was over * million Indian rupees, a stark contrast to destitute category which spent ** thousand Indian rupees. A rich household spent almost ** times that of a destiture household, * times that of an aspirer household, and almost * times that of a middle-class household.
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Context
The dataset presents median household incomes for various household sizes in Indian Wells, CA, 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
https://i.neilsberg.com/ch/indian-wells-ca-median-household-income-by-household-size.jpeg" alt="Indian Wells, CA median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Wells median household income. You can refer the same here
In 2019, the average household size of Hindus in Asia-Pacific was *** people per household. In comparison, Hindus in sub-Saharan Africa had the smallest average household size, at *** people per household. The majority of Hindus live in India.
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Graph and download economic data for Estimate of Median Household Income for Indian River County, FL (MHIFL12061A052NCEN) from 1989 to 2023 about Indian River County, FL; Sebastian; FL; households; median; income; and USA.
The National Family Health Survey (NFHS) was carried out as the principal activity of a collaborative project to strengthen the research capabilities of the Population Reasearch Centres (PRCs) in India, initiated by the Ministry of Health and Family Welfare (MOHFW), Government of India, and coordinated by the International Institute for Population Sciences (IIPS), Bombay. Interviews were conducted with a nationally representative sample of 89,777 ever-married women in the age group 13-49, from 24 states and the National Capital Territoty of Delhi. The main objective of the survey was to collect reliable and up-to-date information on fertility, family planning, mortality, and maternal and child health. Data collection was carried out in three phases from April 1992 to September 1993. THe NFHS is one of the most complete surveys of its kind ever conducted in India.
The households covered in the survey included 500,492 residents. The young age structure of the population highlights the momentum of the future population growth of the country; 38 percent of household residents are under age 15, with their reproductive years still in the future. Persons age 60 or older constitute 8 percent of the population. The population sex ratio of the de jure residents is 944 females per 1,000 males, which is slightly higher than sex ratio of 927 observed in the 1991 Census.
The primary objective of the NFHS is to provide national-level and state-level data on fertility, nuptiality, family size preferences, knowledge and practice of family planning, the potentiel demand for contraception, the level of unwanted fertility, utilization of antenatal services, breastfeeding and food supplemation practises, child nutrition and health, immunizations, and infant and child mortality. The NFHS is also designed to explore the demographic and socioeconomic determinants of fertility, family planning, and maternal and child health. This information is intended to assist policymakers, adminitrators and researchers in assessing and evaluating population and family welfare programmes and strategies. The NFHS used uniform questionnaires and uniform methods of sampling, data collection and analysis with the primary objective of providing a source of demographic and health data for interstate comparisons. The data collected in the NFHS are also comparable with those of the Demographic and Health Surveys (DHS) conducted in many other countries.
National
The population covered by the 1992-93 DHS is defined as the universe of all women age 13-49 who were either permanent residents of the households in the NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed.
Sample survey data
SAMPLE DESIGN
The sample design for the NFHS was discussed during a Sample Design Workshop held in Madurai in Octber, 1991. The workshop was attended by representative from the PRCs; the COs; the Office of the Registrar General, India; IIPS and the East-West Center/Macro International. A uniform sample design was adopted in all the NFHS states. The Sample design adopted in each state is a systematic, stratified sample of households, with two stages in rural areas and three stages in urban areas.
SAMPLE SIZE AND ALLOCATION
The sample size for each state was specified in terms of a target number of completed interviews with eligible women. The target sample size was set considering the size of the state, the time and ressources available for the survey and the need for separate estimates for urban and rural areas of the stat. The initial target sample size was 3,000 completed interviews with eligible women for states having a population of 25 million or less in 1991; 4,000 completed interviews for large states with more than 25 million population; 8,000 for Uttar Pradesh, the largest state; and 1,000 each for the six small northeastern states. In States with a substantial number of backward districts, the initial target samples were increased so as to allow separate estimates to be made for groups of backward districts.
The urban and rural samples within states were drawn separetly and , to the extent possible, sample allocation was proportional to the size of the urban-rural populations (to facilitate the selection of a self-weighting sample for each state). In states where the urban population was not sufficiently large to provide a sample of at least 1,000 completed interviews with eligible women, the urban areas were appropriately oversampled (except in the six small northeastern states).
THE RURAL SAMPLE: THE FRAME, STRATIFICATION AND SELECTION
A two-stage stratified sampling was adopted for the rural areas: selection of villages followed by selection of households. Because the 1991 Census data were not available at the time of sample selection in most states, the 1981 Census list of villages served as the sampling frame in all the states with the exception of Assam, Delhi and Punjab. In these three states the 1991 Census data were used as the sampling frame.
Villages were stratified prior to selection on the basis of a number of variables. The firts level of stratification in all the states was geographic, with districts subdivided into regions according to their geophysical characteristics. Within each of these regions, villages were further stratified using some of the following variables : village size, distance from the nearest town, proportion of nonagricultural workers, proportion of the population belonging to scheduled castes/scheduled tribes, and female literacy. However, not all variables were used in every state. Each state was examined individually and two or three variables were selected for stratification, with the aim of creating not more than 12 strata for small states and not more than 15 strata for large states. Females literacy was often used for implicit stratification (i.e., the villages were ordered prior to selection according to the proportion of females who were literate). Primary sampling Units (PSUs) were selected systematically, with probaility proportional to size (PPS). In some cases, adjacent villages with small population sizes were combined into a single PSU for the purpose of sample selection. On average, 30 households were selected for interviewing in each selected PSU.
In every state, all the households in the selected PSUs were listed about two weeks prior to the survey. This listing provided the necessary frame for selecting households at the second sampling stage. The household listing operation consisted of preparing up-to-date notional and layout sketch maps of each selected PSU, assigning numbers to structures, recording addresses (or locations) of these structures, identifying the residential structures, and listing the names of the heads of all the households in the residentiak structures in the selected PSU. Each household listing team consisted of a lister and a mapper. The listing operation was supervised by the senior field staff of the concerned CO and the PRC in each state. Special efforts were made not to miss any household in the selected PSU during the listing operation. In PSUs with fewer than 500 households, a complete household listing was done. In PSUs with 500 or more households, segmentation of the PSU was done on the basis of existing wards in the PSU, and two segments were selected using either systematic sampling or PPS sampling. The household listing in such PSUs was carried out in the selected segments. The households to be interviewed were selected from provided with the original household listing, layout sketch map and the household sample selected for each PSU. All the selected households were approached during the data collection, and no substitution of a household was allowed under any circumstances.
THE RURAL URBAN SAMPLE: THE FRAME, STRATIFICATION AND SELECTION
A three-stage sample design was adopted for the urban areas in each state: selection of cities/towns, followed by urban blocks, and finally households. Cities and towns were selected using the 1991 population figures while urban blocks were selected using the 1991 list of census enumeration blocks in all the states with the exception of the firts phase states. For the first phase states, the list of urban blocks provided by the National Sample Survey Organization (NSSSO) served as the sampling frame.
All cities and towns were subdivided into three strata: (1) self-selecting cities (i.e., cities with a population large enough to be selected with certainty), (2) towns that are district headquaters, and (3) other towns. Within each stratum, the cities/towns were arranged according to the same kind of geographic stratification used in the rural areas. In self-selecting cities, the sample was selected according to a two-stage sample design: selection of the required number of urban blocks, followed by selection of households in each of selected blocks. For district headquarters and other towns, a three stage sample design was used: selection of towns with PPS, followed by selection of two census blocks per selected town, followed by selection of households from each selected block. As in rural areas, a household listing was carried out in the selected blocks, and an average of 20 households per block was selected systematically.
Face-to-face
Three types of questionnaires were used in the NFHS: the Household Questionnaire, the Women's Questionnaire, and the Village Questionnaire. The overall content
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HCE: Monthly per Capita Consumer Expenditure: Average: Punjab: Rural: Food: Sugar data was reported at 62.610 INR in 2012. This records a decrease from the previous number of 62.630 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: Punjab: Rural: Food: Sugar data is updated yearly, averaging 48.460 INR from Jun 1994 (Median) to 2012, with 4 observations. The data reached an all-time high of 62.630 INR in 2010 and a record low of 23.680 INR in 1994. HCE: Monthly per Capita Consumer Expenditure: Average: Punjab: Rural: Food: Sugar data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB072: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Punjab: Rural (Discontinued).
Most households in India between 2019 and 2021 had between ***** and **** people. The number of ****-people households accounted for over ** percent during the survey period. Interestingly, about **** percent reported **** or more people in one household. Rural areas had a higher share of households with **** or more members.
In 2022, government or private services accounted for the highest source of income at *** thousand Indian rupees in rural households, while livestock rearing was valued at over **** thousand Indian rupees.
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India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Indian Head Park. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Indian Head Park. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2023
In terms of income distribution across age cohorts, in Indian Head Park, the median household income stands at $226,538 for householders within the 25 to 44 years age group, followed by $143,201 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $73,929.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Head Park median household income by age. You can refer the same here
According to a survey conducted in 2015 across India, over ** percent of the surveyed households had an average monthly income up to 10,000 Indian rupees. This percentage varied among the rural and urban areas, where over ** percent of the rural households and ** percent of the urban households earned up to 10,000 Indian rupees monthly. India had a high rate of rural to urban migration, as Indian cities provided better standards of living and employment opportunities.
Multiple income generators
For most of the population, income is earned in form of wages or salary, rent from residential or commercial property, interest from financial investments, and profits from family businesses. Most Indian households have multiple earning members to support consumption expenses on a day to day basis. During the surveyed year, around ** percent of the households had a single earner, mostly the head of the family, followed by about ** percent of households with two earning members.
Employment scenario
There are a lot of uncertainties in the job market in India. Non-availability of jobs matching education and skills was one of the main reasons for unemployment among Indian graduates. Underemployment was also a problem, and it was higher in urban areas than rural ones. Even though a majority of the population was self-employed, most jobs taken by workers had no written job contracts in both the salaried and casual employment sectors.
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HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural: Food data was reported at 621.960 INR in 2012. This records an increase from the previous number of 497.090 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural: Food data is updated yearly, averaging 242.685 INR from Jun 1978 (Median) to 2012, with 6 observations. The data reached an all-time high of 621.960 INR in 2012 and a record low of 44.330 INR in 1978. HCE: Monthly per Capita Consumer Expenditure: Average: India: Rural: Food data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.HB016: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Rural (Discontinued).
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Context
The dataset presents the median household income across different racial categories in Indian Village. 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 Indian Village population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 60% of the total residents in Indian Village. Notably, the median household income for White households is $59,450. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $101,336. This reveals that, while Whites may be the most numerous in Indian Village, Black or African American households experience greater economic prosperity in terms of median household income.
https://i.neilsberg.com/ch/indian-village-in-median-household-income-by-race.jpeg" alt="Indian Village median household income diversity across racial categories">
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Indian Village median household income by race. You can refer the same here
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HCE: Monthly per Capita Consumer Expenditure: Average: Assam: Urban: Non Food: Education data was reported at 107.360 INR in 2012. This records an increase from the previous number of 75.980 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: Assam: Urban: Non Food: Education data is updated yearly, averaging 75.980 INR from Jun 2005 (Median) to 2012, with 3 observations. The data reached an all-time high of 107.360 INR in 2012 and a record low of 48.370 INR in 2005. HCE: Monthly per Capita Consumer Expenditure: Average: Assam: Urban: Non Food: Education data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB025: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Assam: Urban (Discontinued).
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HCE: Monthly per Capita Consumer Expenditure: Average: Madhya Pradesh: Rural: Food: Fruit: Dry data was reported at 3.720 INR in 2012. This records an increase from the previous number of 1.950 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: Madhya Pradesh: Rural: Food: Fruit: Dry data is updated yearly, averaging 1.630 INR from Jun 1994 (Median) to 2012, with 4 observations. The data reached an all-time high of 3.720 INR in 2012 and a record low of 0.350 INR in 1994. HCE: Monthly per Capita Consumer Expenditure: Average: Madhya Pradesh: Rural: Food: Fruit: Dry data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB054: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: Madhya Pradesh: Rural (Discontinued).
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HCE: Monthly per Capita Consumer Expenditure: Average: West Bengal: Rural data was reported at 1,143.180 INR in 2012. This records an increase from the previous number of 855.100 INR for 2010. HCE: Monthly per Capita Consumer Expenditure: Average: West Bengal: Rural data is updated yearly, averaging 708.605 INR from Jun 1994 (Median) to 2012, with 4 observations. The data reached an all-time high of 1,143.180 INR in 2012 and a record low of 278.780 INR in 1994. HCE: Monthly per Capita Consumer Expenditure: Average: West Bengal: Rural data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Domestic Trade and Household Survey – Table IN.HB086: HCES: Uniform Reference Period (URP): Average Monthly Per Capita Consumption Expenditure (MPCE): by Item Group: West Bengal: Rural (Discontinued).
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Estimate of Median Household Income for Indian River County, FL was 73686.00000 $ in January of 2023, according to the United States Federal Reserve. Historically, Estimate of Median Household Income for Indian River County, FL reached a record high of 73686.00000 in January of 2023 and a record low of 26974.00000 in January of 1989. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate of Median Household Income for Indian River County, FL - last updated from the United States Federal Reserve on July of 2025.
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NOTE: For information on confidentiality protection,.nonsampling error, definitions, and count corrections see.http://www.census.gov/prod/cen2000/doc/sf1.pdf
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.
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).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here