78 datasets found
  1. Largest cities in India 2023

    • statista.com
    Updated Jul 4, 2024
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    Statista (2024). Largest cities in India 2023 [Dataset]. https://www.statista.com/statistics/275378/largest-cities-in-india/
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    Dataset updated
    Jul 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    India
    Description

    Delhi was the largest city in terms of number of inhabitants in India in 2023.The capital city was estimated to house nearly 33 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.

  2. Countries with largest increase in urban population until 2050

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Countries with largest increase in urban population until 2050 [Dataset]. https://www.statista.com/statistics/875047/top-ten-countries-with-projected-increase-in-urban-population/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    World
    Description

    This statistic shows the ten countries with the largest increase in the size of the urban population between 2018 and 2050. Based on forecasted population figures, the urban population of India is projected to be around 416 million more in 2050 than it was in 2018.

  3. Population of largest cities APAC 2022, by country

    • statista.com
    Updated Sep 18, 2024
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    Statista (2024). Population of largest cities APAC 2022, by country [Dataset]. https://www.statista.com/statistics/640668/asia-pacific-population-largest-city-by-country/
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    Dataset updated
    Sep 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Asia, Asia–Pacific
    Description

    Japan’s largest city, greater Tokyo, had a staggering 37.27 million inhabitants in 2022, making it the most populous city across the Asia-Pacific region. India had the second largest city after Japan with a population consisting of approximately 32 million inhabitants. Contrastingly, approximately 400 thousand inhabitants populated Papua New Guinea's largest city in 2022.

    A megacity region Not only did Japan and India have the largest cities throughout the Asia-Pacific region but they were among the three most populated cities worldwide in 2023. Interestingly, over half on the world’s megacities were situated in the Asia-Pacific region. However, being home to more than half of the world’s population, it does not seem surprising that by 2025 it is expected that more than two thirds of the megacities across the globe will be located in the Asia Pacific region. Other megacities are also expected to emerge within the Asia-Pacific region throughout the next decade. There have even been suggestions that Indonesia’s Jakarta and its conurbation will overtake Greater Tokyo in terms of population size by 2030.

    Increasing populations Increased populations in megacities can be down to increased economic activity. As more countries across the Asia-Pacific region have made the transition from agriculture to industry, the population has adjusted accordingly. Thus, more regions have experienced higher shares of urban populations. However, as many cities such as Beijing, Shanghai, and Seoul have an aging population, this may have an impact on their future population sizes, with these Asian regions estimated to have significant shares of the population being over 65 years old by 2035.

  4. Population density in India as of 2022, by area and state

    • statista.com
    Updated Jul 10, 2023
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    Statista (2023). Population density in India as of 2022, by area and state [Dataset]. https://www.statista.com/statistics/1366870/india-population-density-by-area-and-state/
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    Dataset updated
    Jul 10, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    India
    Description

    In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.

  5. N

    Comprehensive Median Household Income and Distribution Dataset for Indian...

    • neilsberg.com
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Comprehensive Median Household Income and Distribution Dataset for Indian Village, IN: Analysis by Household Type, Size and Income Brackets [Dataset]. https://www.neilsberg.com/research/datasets/cda3717b-b041-11ee-aaca-3860777c1fe6/
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    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    IN, Indian Village
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    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.

    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).

    • Indian Village, IN Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
    • Median Household Income Variation by Family Size in Indian Village, IN: Comparative analysis across 7 household sizes
    • Income Distribution by Quintile: Mean Household Income in Indian Village, IN
    • Indian Village, IN households by income brackets: family, non-family, and total, 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/.

    Interested in deeper insights and visual analysis?

    Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here

  6. d

    Area and Population: State-wise (Census 2011)

    • dataful.in
    Updated Mar 24, 2025
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    Dataful (Factly) (2025). Area and Population: State-wise (Census 2011) [Dataset]. https://dataful.in/datasets/485
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    csv, application/x-parquet, xlsxAvailable download formats
    Dataset updated
    Mar 24, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Area
    Description

    The data shows for each state/union territory the area, population by gender and population by urban/rural.

    Note: The area figures of States and U.T's do not add up to area of India because : (i) The shortfall of 7 square km. area of Madhya Pradesh and 3 square km. area of Chhattisgarh is yet to be resolved by the Survey of India. (ii) Disputed area of 13 square km. between Pondicherry and Andhra Pradesh is neither included in Pondicherry nor in Andhra Pradesh. For All India: 1) The population figures excludes population of the area under unlawful occupation of Pakistan and China where Census could not be taken. 2) Area figures includes the area under unlawful occupation of Pakistan and China. The area includes 78,114 sq.km. under illegal occupation of Pakistan, 5,180 sq. km.illegally handed over by Pakistan to China and 37,555 sq.km. under illegal occupation of China.

  7. Population of Delhi metro area India 1960-2024

    • statista.com
    Updated Nov 25, 2024
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    Statista (2024). Population of Delhi metro area India 1960-2024 [Dataset]. https://www.statista.com/statistics/911017/india-population-in-delhi/
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    Dataset updated
    Nov 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    As of the year 2024, the population of the capital city of India, Delhi was over 33 million people. This was a 2.63 percent growth from last year. The historical trends show that the population doubled between 1990 and 2010. However, the population growth rate in the last three years has been the lowest since the recorded period starting in 1960. The UN estimated that the population was expected to reach around 35 million by 2030. Reasons for population growth   As per the Delhi Economic Survey, migration added over 200 thousand people to Delhi’s population in 2022. The estimates showed relative stability in natural population growth for a long time before the pandemic. The numbers suggest a sharp decrease in birth rates from 2020 onwards and a corresponding increase in death rates in 2021 due to the Covid-19 pandemic. The net natural addition or the remaining growth is attributed to migration. These estimates are based on trends published by the Civil Registration System. National Capital Region (NCR) Usually, population estimates for Delhi represent the urban agglomeration of Delhi, which includes Delhi and some of its adjacent suburban areas. The National Capital Region or NCR is one of the largest urban agglomerations in the world. It is an example of inter-state regional planning and development, centred around the National Capital Territory of Delhi, and covering certain districts of neighbouring states Haryana, Uttar Pradesh, and Rajasthan. Noida, Gurugram, and Ghaziabad are some of the key cities of NCR. Over the past decade, NCR has emerged as a key economic centre in India.

  8. i

    National Family Health Survey 1992-1993 - India

    • catalog.ihsn.org
    • dev.ihsn.org
    • +2more
    Updated Jul 6, 2017
    + more versions
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    International Institute for Population Sciences (IIPS) (2017). National Family Health Survey 1992-1993 - India [Dataset]. https://catalog.ihsn.org/catalog/2547
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    International Institute for Population Sciences (IIPS)
    Time period covered
    1992 - 1993
    Area covered
    India
    Description

    Abstract

    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.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Data collected for women 13-49, indicators calculated for women 15-49

    Universe

    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.

    Kind of data

    Sample survey data

    Sampling procedure

    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.

    Mode of data collection

    Face-to-face

    Research instrument

    Three types of questionnaires were used in the NFHS: the Household Questionnaire, the Women's Questionnaire, and the Village Questionnaire. The overall content

  9. Enterprise Survey of Micro Firms 2022 - India

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Feb 6, 2025
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    Enterprise Survey of Micro Firms 2022 - India [Dataset]. https://microdata.worldbank.org/index.php/catalog/6495
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    Dataset updated
    Feb 6, 2025
    Dataset provided by
    World Bankhttp://worldbank.org/
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank Group (WBG)
    Time period covered
    2021 - 2022
    Area covered
    India
    Description

    Abstract

    The Enterprise Surveys of Micro firms (ESM) conducted by the World Bank Group's (WBG) Enterprise Analysis Unit (DECEA) in India. The survey covers nine cities: Hyderabad, Telangana; Jaipur, Rajasthan; Kochi, Kerala; Ludhiana, Punjab; Mumbai, Maharashtra; Sehore, Madhya Pradesh; Surat, Gujarat; Tezpur, Assam; and Varanasi, Uttar Pradesh.

    The primary objectives of the ESM are to: i) understand demographics of the micro enterprises in the covered cities, ii) describe the environment within which these enterprises operate, and iii) enable data analysis based on the samples that are representative at each city level.

    Geographic coverage

    Nine cities in India: Hyderabad, Telangana; Jaipur, Rajasthan; Kochi, Kerala; Ludhiana, Punjab; Mumbai, Maharashtra; Sehore, Madhya Pradesh; Surat, Gujarat; Tezpur, Assam; and Varanasi, Uttar Pradesh.

    Analysis unit

    • Firms

    Universe

    The universe of ESM includes formally registered businesses in the sectors covered by the ES and with less than five employees. The definition of formal registration can vary by country. The universe table for each of the nine cities covered by ESM in India was obtained from the 6th Economic Census (EC) of India (conducted between January 2013 and April 2014), which has its own well-defined definition of registration. Generally, this entails registration with any central/government agency, under Shops & Establishment Act, Factories Act etc.

    In terms of sectors, the survey covers all non-agricultural and non-extractive sectors. In particular, according to the group classification of ISIC Revision 4.0, it includes: all manufacturing sectors (group D), construction (group F), wholesale and retail trade (group G), transportation and storage (group H), accommodation and food service activities (group I), a subset of information and communications (group J), some administrative and support service activities (codes 79) and other service activities (codes 95). Notably, the ESM universe excludes the following sectors: financial and insurance activities (group K), real estate activities (group L), and all public or utilities-sectors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for Enterprise Survey of Micro firms in India 2022 was selected using stratified random sampling, following the methodology explained in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling was preferred over simple random sampling for several reasons, including: a. To obtain unbiased estimates for different subdivisions of the population with some known level of precision, along with the unbiased estimates for the whole population. b. To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions. c. To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.) d. Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous. e. The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.

    Two levels of stratification were used in this survey: industry and region. For stratification by industry, two groups were used: Manufacturing (combining all the relevant activities in ISIC Rev. 4.0 codes 10-33) and Services (remainder of the universe, as outlined above). Regional stratification was done across nine cities included in the study, namely: Hyderabad, Jaipur, Kochi, Ludhiana, Mumbai, Sehore, Surat, Tezpur and Varanasi.

    Mode of data collection

    Face-to-face [f2f]

  10. Urbanization in India 2023

    • statista.com
    Updated Feb 13, 2025
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    Statista (2025). Urbanization in India 2023 [Dataset]. https://www.statista.com/statistics/271312/urbanization-in-india/
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    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    In 2023, approximately a third of the total population in India lived in cities. The trend shows an increase of urbanization by more than 4 percent in the last decade, meaning people have moved away from rural areas to find work and make a living in the cities. Leaving the fieldOver the last decade, urbanization in India has increased by almost 4 percent, as more and more people leave the agricultural sector to find work in services. Agriculture plays a significant role in the Indian economy and it employs almost half of India’s workforce today, however, its contribution to India’s GDP has been decreasing while the services sector gained in importance. No rural exodus in sightWhile urbanization is increasing as more jobs in telecommunications and IT are created and the private sector gains in importance, India is not facing a shortage of agricultural workers or a mass exodus to the cities yet. India is a very densely populated country with vast areas of arable land – over 155 million hectares of land was cultivated land in India as of 2015, for example, and textiles, especially cotton, are still one of the major exports. So while a shift of the workforce focus is obviously taking place, India is not struggling to fulfill trade demands yet.

  11. i

    National Sample Survey 1993 (49th Round) - Schedule 0.21 - Particulars of...

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
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    National Sample Survey Office (2019). National Sample Survey 1993 (49th Round) - Schedule 0.21 - Particulars of Slum - India [Dataset]. http://catalog.ihsn.org/catalog/2628
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Sample Survey Office
    Time period covered
    1993
    Area covered
    India
    Description

    Abstract

    A nationwide survey on "Particulars of Slums" was carried-out by the National Sample Survey Organisation (NSSO) during the period January-June, 1993 in its 49th round to ascertain the extent of civic facilities available in the slums. The 49th round survey among other objectives also collected data on the condition of slum dwellings as well as on some general particulars of slum areas. Apart from formulating the sampling design with an emphasis to obtain an adequate number of slum households for the survey on housing condition and migration, surveyed the slum areas and collected information on slums. The schedule 0.21 was canvassed in both the rural and urban areas. All the slums, both the declared ones as well as the others (undeclared), found in the selected first stage units were surveyed even if hamlet-group/sub-block selection was resorted to in some of then. To ascertain the extent of civic facilities available in the slums as well as the information regarding the improvement of slum condition during a period of last five years was also collected. Information was collected by contacting one or more knowledgeable persons in the FSU on the basis of predominant criterion in both declared and undeclared slums, and not through household approach.

    Geographic coverage

    The geographical coverage of the survey was the whole of the Indian Union except Ladakh & Kargil districts of Jammu & Kashmir, 768 interior villages of Nagaland and 172 villages in Andaman & Nicobar islands which remain inaccessible throughout the year. However, certain districts of Jammu & Kashmir viz. Doda, Anantanag, Pulwama, Srinagar, Badgam, Barmula & Kupwara, as well as Amritsar district in Punjab, had to be excluded from the survey coverage due to unfavourable field conditions.

    Sampling procedure

    Sample Design : The first stage units in the rural sector and urban sector were census villages and urban frame survey (UFS) blocks respectively. However for newly declared towns of the 1991 census,for which UFS frames were not available, census EBs were used as first stage units.

    Sampling frame for fsu's : In the rural sector, the sampling frame in most of the districts was the 1981 census list of villages. However, in Assam and in 8 districts of Madhya Pradesh, 1971 Census lists of villages were used. For Nagaland, the villages situated within 5 kms of a bus route constituted the sampling frame. For the Andaman & Nicobar islands the list of accessible villages was used as sampling frame. In the urban sector, the lists of NSS urban frame survey (UFS) blocks were the sampling frames used in most cases. However, 1991 Census house - listing enumeration blocks were considered as the sampling units for some of the newly declared towns of the 1991 population census, for which UFS frames were not available.

    Stratification : Each state/u.t. was divided into one or more agro-economic regions by grouping contiguous districts which are similar with respect to population density and crop pattern. In Gujarat, however, some districts were subdivided for the purpose of region formation on the basis of location of dry areas and the distribution of tribal population in the state. The total number of regions formed in the whole of India was 78.

    In the rural sector, within each region, each district with a rural population of less than 1.8 million according to the 1981 Census formed a single basic stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils, similar as far as possible in respect of rural population density & crop pattern. In Gujarat, however, in the case of districts extending over more than one region, the portion of a district falling in each region constituted a separate stratum even if the rural population of the district as a whole was less than 1.8 million. Further, in Assam, the strata formed for the earlier NSS round on the basis of 1971 Census rural population exactly in the above manner, but with a cutoff point of 1.5 million population, were retained as the strata for rural sampling.

    In the urban sector, strata were formed, within NSS regions, on the basis of 1981 (1991 in some of the new towns) Census population. Each city with a population of 10 lakhs or more formed a separate stratum itself. The remaining towns of each region were grouped to form three different strata on the basis of 1981 (1991 in a few cases) census population.

    Sub stratification of urban strata : In order to be able to allocate a large proportion of the first stage sample to slum-dominated areas than would otherwise be possible, each stratum in the urban sector was divided into two "sub-strata" a s follows. Sub-stratum 1 was constituted of the UFS blocks in the stratum with a "slum area" indicated in the frame. Substratum 2 was constituted of the remaining blocks of the stratum.

    Allocation of sample : A total all-India sample of 8000 first stage units (5072 villages and 2928 urban blocks) determined on the basis of investigator strength in different state/u.t's and the expected workload per investigator was first allocated to the states/u.t's in proportion to Central Staff available. The sample thus obtained for each state/u.t. was then allocated to its rural & urban sectors considering the relative sizes of the rural & urban population with double weightage for the urban sector. Within each sector of a state/u.t., the allotted sample size was reallocated to the different strata in proportion to stratum population. Stratum-level allocations were adjusted so that the sample size for a stratum (rural or urban) was at least a multiple of 4. This was done in order to have equal sized samples in each sub-sample and sub-round.

    In the urban sector, stratum-level allocations were further allocated to the two sub-strata in proportion to the number of UFS blocks in the sub-strata, with double weightage to sub-stratum 1, with a minimum sample size of 4 blocks to sub-stratum 1 (2 if stratum allocation was only 4). Sub-stratum level allocations were made even in number.

    Selection of fsu's : Sample villages except in Arunachal Pradesh were selected by pps systematic sampling with population as the size variable and sample blocks by simple random sampling without replacement. In both sectors the sample of fsu's was drawn in the form of two independent sub-samples. (In Arunachal Pradesh the sample of villages was drawn by a cluster sampling procedure. The field staff were supplied with a list of sample "nucleus" villages and were advised to select cluster of villages building up each cluster around a nucleus village according to prescribed guidelines. The nucleus villages were selected circular-systematically with equal probability in the form of two ) independent sub-samples.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire consisted of 6 blocks (including 0) as given below : Block - 0 : descriptive identification of sample village/block having slum Block - 1 : identification of sample village/block having slum. Block - 3 : Remarks by investigator. Block - 4 : Comments by Supervisory Officer(s). Block - 5 : Particulars about slum.

    Response rate

    1572 slums spread over 5072 villages and 2928 urban blocks in the sample have been surveyed.

  12. National Sample Survey 2004-2005 (61st round) - Schedule 1.0 - Consumer...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Mar 29, 2019
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    National Sample Survey Organisation (2019). National Sample Survey 2004-2005 (61st round) - Schedule 1.0 - Consumer Expenditure - India [Dataset]. https://datacatalog.ihsn.org/catalog/1910
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Sample Survey Organisation
    Time period covered
    2004 - 2005
    Area covered
    India
    Description

    Geographic coverage

    The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

    Analysis unit

    Household, individual

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample Design Outline of sample design: A stratified multi-stage design has been adopted for the 61st round survey. The first stage units (FSU) are the 2001 census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In the case of large villages/blocks requiring hamlet-group (hg)/sub-block (sb) formation, one intermediate stage is the selection of two hgs/sbs from each FSU.

    Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks has been considered as the sampling frame.

    Stratification: Within each district of a State/UT, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them will also form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. There are 27 towns with population 10 lakhs or more at all-India level as per census 2001.

    Sub-stratification:
    Rural sector: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed is 'r/2'. The villages within a district as per frame have been first arranged in ascending order of population. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprises a group of villages of the arranged frame and has more or less equal population.

    Urban sector: If 'u' be the sample size for a urban stratum, 'u/2' number of sub-strata have been formed. The towns within a district, except those with population 10 lakhs or more, have been first arranged in ascending order of population. Next, UFS blocks of each town have been arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of UFS blocks.

    For towns with population 10 lakhs or more, the urban blocks have been first arranged by IV unit no. × block no. in ascending order. Then 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of blocks.

    Total sample size (FSUs): 12784 FSUs have been allocated at all-India level on the basis of investigator strength in different States/UTs for central sample and 14992 for state sample.

    Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

    Allocation of State/UT level sample to rural and urban sectors: State/UT level sample size is allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs has been allocated to each state/UT separately for rural and urban areas.

    Allocation to strata: Within each sector of a State/UT, the respective sample size is allocated to the different strata in proportion to the stratum population as per census 2001. Allocations at stratum level have been adjusted to a multiple of 4 with a minimum sample size of four.

    Selection of FSUs: Two FSUs have been selected from each sub-stratum of a district of rural sector with Probability Proportional to Size With Replacement (PPSWR), size being the population as per Population Census 2001. For urban sector, two FSUs have been selected from each sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR). Within each sub-stratum, samples have been drawn in the form of two independent sub-samples in both the rural and urban sectors.

    Note: Detail sampling procedure is provided as external resource.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Schedule 1.0 - Consumer Expenditure

    Block 0- Descriptive identification of sample household: This block is meant for recording descriptive identification particulars of a sample household. Block 1- Identification of sample households Block 2- Particulars of field operations: The identity of the Investigator, the Assistant Superintendent and the Superintendent associated with the work, date of survey/inspection/scrutiny of schedules, date of despatch, etc., have been recorded in this block against the appropriate items in the relevant columns. Block 3- Household characteristics: The characteristics to be recorded in this block are mainly intended to be used to classify the households for tabulation.

    Block 4- Demographic and other particulars of household members: All members of the sample household have been listed in this block. Demographic particulars (relation to head, sex, age, marital status and general education) and number of meals taken recorded for each member using one line for one member.

    Blocks 5 to 11- Blocks on Consumer Expenditure: Consumption of different broad groups of items recorded in different blocks (5 to 11) according to the appropriate "approach". There have been two different reference periods for data collection in case of certain groups of items and only one reference period for other groups.

    • Block 5- Consumption of food, pan, tobacco and intoxicants during the last 30 days: In this block information on consumption of each item of food, pan, tobacco and intoxicants by the household have been collected for a reference period of 30 days preceding the date of survey
    • Block 6- Consumption of fuel and light during the last 30 days: In this block, information on consumption of fuel and light collected for the household during the 30 days prior to the date of survey.
    • Block 7- Consumption of clothing, bedding, etc.: In this block, information on quantity and value of consumption of all items of clothing collected for two reference periods; last 30 days and last 365 days.
    • Block 8- Consumption of footwear: In this block, information on quantity and value of consumption of footwear have been collected for two reference periods; last 30 days and last 365 days.
    • Block 9- Expenditure on education and medical (institutional) goods and services: In this block, information on education and institutional medical expenses incurred during the last 30 days and last 365 days have been collected.
    • Block 10- Expenditure on miscellaneous goods and services including medical (non-institutional), rents and taxes during the last 30 days: In this block, relating to miscellaneous goods and services, information have been collected on the expenditure for purchase of these items during the reference period.
    • Block 11- Expenditure for purchase and construction (including repair and maintenance) of durable goods for domestic use: Information on expenditure incurred for purchase and cost of raw materials and services for construction and repairs of durable goods for domestic use have been collected in this block for both last 30 days and last 365 days.

    Block 12- Perception of household regarding sufficiency of food

    Block 13- Summary of consumer expenditure Block 14- Remarks by investigator Block 15- Comments by supervisory officer(s)

  13. National Sample Survey 2002 (58th Round) - Schedule 26 - Disabled Persons -...

    • catalog.ihsn.org
    • dev.ihsn.org
    Updated Mar 29, 2019
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    National Sample Survey Organisation (2019). National Sample Survey 2002 (58th Round) - Schedule 26 - Disabled Persons - India [Dataset]. http://catalog.ihsn.org/catalog/3227
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Sample Survey Organisation
    Time period covered
    2002
    Area covered
    India
    Description

    Abstract

    The National Sample Survey Organisation (NSSO) carried out the first country wide comprehensive survey of physically disabled persons during the 36th round survey (July - December, 1981). The next survey on the subject was carried out after a period of ten years in NSS 47th round (July - December, 1991). In NSS 36th and 47th round surveys, information was collected on three types of physical disabilities - visual, communication and locomotor - along with the cause of disability, aid/appliance acquired by the disabled, general and vocational educational level of the disabled etc. In addition, data on developmental milestones and behavioural pattern of all children of age 5-14 years, regardless of whether they were physically disabled or not, were collected.

    The Ministry of Social Justice and Empowerment (MSJE) made a request for conducting a survey on disability in order to meet the data needs for evolving specific strategies and interventions during the 10th Five Year Plan. The need for a detailed survey on disability was strongly felt by MSJE since its data requirement included not only the number of disabled persons, but also the socio-economic characteristics of the disabled persons such as their age structure, literacy, vocational training, employment, causative factors of disability, age at the onset of disability etc. Keeping in view the urgent data need of the MSJE, the Governing Council of NSSO, in its 81st meeting, decided that the survey on disability may also be carried out as a part of NSS 58th round during July - December 2002. It has been decided that: (i) The survey of disabled persons will also cover persons with mental disability apart from the physically disabled persons since the Ministry of Social Justice and Empowerment (MSJE) also requested for information on mentally disabled persons. The decision to include mental disability in the survey has been taken on the basis of a pre-test of the questions on mental disability, both for the listing and detailed schedules, carried out in the four cities of Kolkata, Mumbai, Hyderabad and Delhi.

    (ii) The information for different types of disabilities is to be collected for persons of all age-groups. Separate information on the developmental milestones of children will not be collected.

    Geographic coverage

    The survey covered the whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample Design

    Outline of Sample Design

    A stratified multi-stage design was adopted for the conduct of survey of NSS 58th round. The first-stage units were census villages (panchayat wards for Kerala) in the rural sector and the NSSO Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units were households in both the sectors.

    Sampling Frame for First-Stage Units

    For the rural sector, the list of Census 1991 villages (panchayat wards for Kerala) and Census 1981 villages for J & K constituted the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks was considered as the sampling frame.

    Stratification

    Rural sector: Two special strata were formed as given below at the State/ UT level on the basis of Population Census 1991 viz. Stratum 1: all FSUs with population between 0 to 50, and Stratum 2: FSUs with population more than 15,000 The special stratum 1 was formed if at least 50 such FSU's were found in a State/UT. Similarly, special stratum 2 was formed if at least 4 such FSUs were found in a State/UT. Otherwise, such FSUs were merged with the general strata. From the remaining FSUs (not covered under stratum 1 &2) general strata (hereafter, stratum will refer to general stratum unless otherwise mentioned) was formed and numbered 3, 4, 5 …. etc. (even if no special strata have been formed). Each district of a State/UT was normally treated as a separate stratum. However, if the provisional population of the district was greater than or equal to 2.5 million as per Census 2001, the district was divided into two or more strata with more or less equal population as per population census 1991 by grouping contiguous tehsils. However, in Gujarat, some districts were not wholly included in an NSS region. In such cases, the part of the district falling in an NSS region constituted a separate stratum.

    Urban sector: In the urban sector, stratum was formed within each NSS region on the basis of size class of towns as per Census 1991 town population except for towns specified in Table 4. The stratum number and their composition (within each region) are given below: stratum 1: all towns with population (P) < 0.1 million
    stratum 2: all towns with 0.1= P < 0.5 million
    stratum 3: all towns with 0.5= P < 1 million
    stratum 4,5,6, … each town with P= 1 million
    The stratum numbers was retained as above even if, in some regions, some of the stratum is not formed.

    Sub-stratification

    There was no sub-stratification in the rural sector. However, to cover more number of households living in slums, in urban sector each stratum was divided into 2 sub-strata as follows: sub-stratum 1: all UFS blocks having area type 'slum area' sub-stratum 2: remaining UFS blocks If there was one UFS block with area type 'slum area' within a stratum, sub-stratum 1 was not formed; it was merged with sub-stratum 2.

    Total sample size (FSUs)

    A total number of 8338 and 9076 first-stage units were selected for survey in the Central and State samples respectively.

    Allocation of total sample to States and UTs

    The total sample FSUs was allocated to the States and UTs in proportion to provisional population as per Census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

    Allocation of State/ UT level sample to Rural and Urban sectors

    State/UT level sample was allocated between two sectors in proportion to provisional population as per Census 2001 with double weightage to urban sector.

    Allocation of Rural /Urban sector level sample size to strata / sub-strata

    Both rural and urban sector samples allotted to a State/UT were allocated to different strata in proportion to population of the stratum. All the stratum-level allocations were adjusted to multiple of 2. Stratum-level sample size in the urban sector was further allocated to 2 sub-strata in proportion to the number of UFS blocks in them with double weightage to sub-stratum 1 subject to a minimum sample size of 2 or 4 to sub-stratum 1 according as stratum-level allocation is 4 or greater than 4. Sub-stratum level allocations in the urban sector were made even.

    Selection of FSUs

    FSUs were selected in the form of two independent sub-samples in both the sectors. For special stratum 2 and all the general strata of rural sector, FSUs were selected by probability proportional to size with replacement (PPSWR) where size was the 1991 census population. For urban sector and special stratum 1 of rural sector, FSUs were selected by simple random sampling without replacement (SRSWOR).

    Selection of hamlet-groups/sub-blocks / households

    Formation of hamlet-group/sub-block

    Large villages/ blocks having approximate present population 1200 or more were divided into a suitable number of hamlet-groups/sub-blocks as given below: approximate present population no. of hamlet-groups/ sub-blocks formed
    less than 1200 1 (no hamlet-group/sub-block formation)
    1200 to 1799 3
    1800 to 2399 4
    2400 to 2999 5
    3000 to 3599 6
    ....and so on

    For rural areas of Himachal Pradesh, Sikkim and Poonch, Rajouri, Udhampur and Doda districts of Jammu and Kashmir and Idukki district of Kerala where habitation pattern causes difficulty in listing due to topography of the area, hg formation criterion was relaxed for which number of hamlet groups formed as per population criterion is given below: approximate present population no. of hamlet-groups/ sub-blocks formed
    less than 600 1 (no hamlet-group/sub-block formation)
    600 to 899 3
    900 to 1199 4
    1200 to 1499 5
    ....and so on

    Hamlet-groups / sub-blocks were formed by more or less equalising population. For large urban blocks, the sub-block (sb) having slum dwellers, if any, was selected with probability 1 and was termed as segment 1. However, if there were more than one sb having slum dwellers, the sb having maximum number of slum dwellers was selected as segment 1. After selection of sb for segment 1, one more sb was selected by simple random sampling (SRS) from the remaining sb's of the block and was termed as segment 2. For large blocks (having no slum areas) two sub-blocks were selected by simple random sampling without replacement (SRSWOR) and were combined to form segment 2. For urban blocks without sub-block formation, segment number was 1 or 2 depending on whether the block was having a slum or not. For large villages two hamlet-groups were selected by SRSWOR and were combined to form segment 2. For villages without hamlet-group formation, segment number was also 2. The segments were considered separately for listing and selection of the ultimate-stage units.

    Formation of Second Stage Strata (SSS) and selection of households for schedule 26

    In each selected village/block/segment, three second stage strata (SSS) were formed on the basis of disability type. The number of households selected is given below: Without segment formation with segment formation (for each segment)

    SSS 1: households

  14. Urban slum population in India 2011, by major cities

    • statista.com
    Updated May 17, 2024
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    Statista (2024). Urban slum population in India 2011, by major cities [Dataset]. https://www.statista.com/statistics/1399410/india-urban-slum-population-by-city/
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    Dataset updated
    May 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2011
    Area covered
    India
    Description

    As per the Census data dated 2011, the slum dwellers population in Mumbai was the highest among all other major metropolitan cities of India, at around five million. Hyderabad and Delhi followed it. A total of about 65 million people were estimated to be living in slums across the country.

  15. i

    National Sample Survey 2004-2005 (61st round) - Schedule 10 - Employment and...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
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    National Sample Survey Organization (NSSO) (2019). National Sample Survey 2004-2005 (61st round) - Schedule 10 - Employment and Unemployment - India [Dataset]. http://datacatalog.ihsn.org/catalog/2316
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Sample Survey Organization (NSSO)
    Time period covered
    2004 - 2005
    Area covered
    India
    Description

    Abstract

    The 61st round of the Nationbal Sample Survey was conducted during July, 2004 to June, 2005. The survey was spread over 7,999 villages and 4,602 urban blocks covering 1,24,680 households (79,306 in rural areas and 45,374 in urban areas) and enumerating 6,02,833 persons (3,98,025 in rural areas and 2,04,808 in urban areas). Employment and unemployment were measured with three different approaches, viz. usual status with a reference period of one year, current weekly status with one week reference period and current daily status based on the daily activity pursued during each day of the reference week. Unless otherwise stated, ‘all’ usual status workers will mean all workers taking into consideration the usual principal and subsidiary status taken together.

    Geographic coverage

    The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

    Analysis unit

    Household, individual

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Outline of sample design: A stratified multi-stage design has been adopted for the 61st round survey. The first stage units (FSU) are the 2001 census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In the case of large villages/blocks requiring hamlet-group (hg)/sub-block (sb) formation, one intermediate stage is the selection of two hgs/sbs from each FSU.

    Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks has been considered as the sampling frame.

    Stratification: Within each district of a State/UT, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them will also form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. There are 27 towns with population 10 lakhs or more at all-India level as per census 2001.

    Sub-stratification:

    • Rural sector: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed is 'r/2'. The villages within a district as per frame have been first arranged in ascending order of population. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprises a group of villages of the arranged frame and has more or less equal population.

    • Urban sector: If 'u' be the sample size for a urban stratum, 'u/2' number of sub-strata have been formed. The towns within a district, except those with population 10 lakhs or more, have been first arranged in ascending order of population. Next, UFS blocks of each town have been arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of UFS blocks.

    For towns with population 10 lakhs or more, the urban blocks have been first arranged by IV unit no. × block no. in ascending order. Then 'u/2' number of sub-strata has been formed in such a way that each sub-stratum has more or less equal number of blocks.

    Total sample size (FSUs): 12784 FSUs have been allocated at all-India level on the basis of investigator strength in different States/UTs for central sample and 14992 for state sample.

    Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to the availability of investigators ensuring more or less uniform work-load.

    Allocation of State/UT level sample to rural and urban sectors: State/UT level sample size is allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs has been allocated to each state/UT separately for rural and urban areas.

    Allocation to strata: Within each sector of a State/UT, the respective sample size is allocated to the different strata in proportion to the stratum population as per census 2001. Allocations at stratum level have been adjusted to a multiple of 4 with a minimum sample size of 4.

    Selection of FSUs: Two FSUs have been selected from each sub-stratum of a district of rural sector with Probability Proportional to Size With Replacement (PPSWR), size being the population as per Population Census 2001. For urban sector, two FSUs have been selected from each sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR). Within each sub-stratum, samples have been drawn in the form of two independent sub-samples in both the rural and urban sectors.

    Selection of hamlet-groups/sub-blocks/households - important steps

    Criterion for hamlet-group/sub-block formation: Large villages/blocks having approximate present population of 1200 or more will be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector as stated below.

    approximate present population of the sample village/block / no. of hgs/sbs to be formed (D)

    less than 1200 (no hamlet-groups/sub-blocks): 1
    1200 to 1799: 3 1800 to 2399: 4 2400 to 2999: 5 3000 to 3599: 6 …..and so on

    For rural areas of Himachal Pradesh, Sikkim and Poonch, Rajouri, Udhampur, Doda districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups formed is as follows.

    approximate present population of the sample village / no. of hgs to be formed

    less than 600 (no hamlet-groups): 1
    600 to 899: 3
    900 to 1199: 4
    1200 to 1499: 5 …..and so on

    Two hamlet-groups/sub-blocks are selected from a large village/UFS block wherever hamlet-groups/sub-blocks have been formed, by SRSWOR. Listing and selection of the households are done independently in the two selected hamlet-groups/sub-blocks. In case hamlet-groups/sub-blocks are to be formed in the sample FSU, the same would be done by more or less equalizing population.

    Formation of Second Stage Strata and allocation of households

    For both Schedule 1.0 and Schedule 10, households listed in the selected village/block/ hamlet-groups/sub-blocks are stratified into three second stage strata (SSS) as given below.

    Rural: The three second-stage-strata (SSS) in the rural sector are formed in the following order:

    SSS 1: relatively affluent households
    SSS 2: from the remaining households, households having principal earning from non- agricultural activity
    SSS 3: other households

    Urban: In the urban sector, the three second-stage strata (SSS) are formed as under:

    Two cut-off points, say 'A' and 'B', based on MPCE of NSS 55th round, have been determined at NSS Region level in such a way that top 10% of households have MPCE more than 'A' and bottom 30% have MPCE less than 'B'. Then three second-stage-strata (SSS) are formed in the urban sector in the following order:

    SSS 1: households with MPCE more than A (i.e. MPCE > A)
    SSS 2: households with MPCE equal to or less than A but equal to or more than B ( i.e. B = MPCE = A)
    SSS 3: households with MPCE less than B (i.e. MPCE < B)

    The number of households to be surveyed in each FSU is 10 for each of the schedules 1.0 and 10. C

    Selection of households for Schedules 1.0 and 10: From each SSS the sample households for both the schedules are selected by SRSWOR. If a household is selected both for schedule 1.0 and schedule 10, only schedule 1.0 would be canvassed in that household and the sample household for schedule 10 would be replaced by next household in the frame for schedule 10.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    In the present round, Schedule 10 on employment-unemployment consists of 16 blocks.

    The first three blocks, viz. Blocks 0, 1 and 2, are used to record identification of sample households and particulars of field operations, as is the common practice in usual NSS rounds. Similarly, the last two blocks, viz., Blocks 10 & 11, are again the usual blocks to record the remarks of investigator and comments by supervisory officer(s), respectively. Block 3 will be for recording the household characteristics like household size, religion, social group, land possessed and cultivated, monthly per capita consumer expenditure, etc., and Block 3.1 for recording particulars of indebtedness of rural labour households.

    Block 4 is used for recording the demographic particulars and attendance in educational institutions of all the household members. Particulars of vocational training receiving/received by the household members will also be collected in block 4.

    In Block 5.1, particulars of usual principal activity of all the household members will be recorded along with some particulars of the enterprises in which the usual status workers (excluding those in crop and plantation activities) are engaged. Information on informal employment will also be collected in block 5.1. Similarly, the particulars of one subsidiary economic activity of the household members along with some

  16. f

    Population Density, Climate Variables and Poverty Synergistically Structure...

    • plos.figshare.com
    • data.subak.org
    tiff
    Updated Jun 2, 2023
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    Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India [Dataset]. https://plos.figshare.com/articles/dataset/Population_Density_Climate_Variables_and_Poverty_Synergistically_Structure_Spatial_Risk_in_Urban_Malaria_in_India/4276937
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    tiffAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS Neglected Tropical Diseases
    Authors
    Mauricio Santos-Vega; Menno J Bouma; Vijay Kohli; Mercedes Pascual
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    India
    Description

    BackgroundThe world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria.Methodology/principal findingsStatistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors.Conclusion/significanceClimate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission ‘hotspots’. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a “radical cure”.

  17. Population density in India 2012-2022

    • statista.com
    Updated Jan 3, 2025
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    Statista (2025). Population density in India 2012-2022 [Dataset]. https://www.statista.com/statistics/271311/population-density-in-india/
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    Dataset updated
    Jan 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    In 2022, the population density in India remained nearly unchanged at around 479.43 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density is calculated by dividing the total population by the total land area, to show the average number of people living there per square kilometer of land.Find more key insights for the population density in countries like Sri Lanka and Pakistan.

  18. i

    National Sample Survey 2011-2012 (68th round) - Schedule 1.0 (Type 1) -...

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 16, 2022
    + more versions
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    National Sample Survey Organization (NSSO) (2022). National Sample Survey 2011-2012 (68th round) - Schedule 1.0 (Type 1) - Consumer Expenditure - India [Dataset]. https://datacatalog.ihsn.org/catalog/3281
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    Dataset updated
    Jun 16, 2022
    Dataset authored and provided by
    National Sample Survey Organization (NSSO)
    Time period covered
    2011 - 2012
    Area covered
    India
    Description

    Abstract

    Objective of the consumer expenditure survey (CES): Firstly, as an indicator of level of living, monthly per capita expenditure (MPCE) is both simple and universally applicable. Average MPCE of any sub-population of the country (any region or population group) is a single number that summarises the level of living of that population. It is supplemented by the distribution of MPCE, which highlights the differences in level of living of the different parts of the population. More detailed analysis of the distribution of MPCE reveals the proportion and absolute numbers of the poor with respect to a given poverty line. A welfare state has to take note of these numbers in allocating its resources among sectors, regions, and socio-economic groups. The distribution of MPCE can also be used to measure the level of inequality, or the degree to which consumer expenditure is concentrated in a small proportion of households or persons, and this can be done without any predetermined poverty line or welfare norms.

    If socialism was the ideal of the 1950's, the ideal of policy-makers during the last decade was "inclusive growth". Increasingly, inclusive growth is seen as the all-important target that we should aim at, at least for the immediate future. Not surprisingly, the NSS CES is being used by scholars as a searchlight focused on the country's development process that shows up just how inclusive the country's growth has been.

    Since the data is collected not only on consumption level but also on the pattern of consumption, the CES has another important use. To work out consumer price indices (CPIs) which measure the general rise in consumer prices, one needs to know not only the price rise for each commodity group but also the budget shares of different commodity groups (used as weights). The budget shares as revealed by the NSS CES are being used for a long time to prepare what is called the weighing diagram for official compilation of CPIs. More extensive use of NSS CES data is planned to have a weighing diagram that uses a finer commodity classification, to prepare rural and urban CPIs separately for each State.

    Apart from these major uses of the CES, the food (quantity) consumption data are used to study the level of nutrition of different regions, and disparities therein. Further, the budget shares of a commodity at different MPCE levels are used by economists and market researchers to determine the elasticity (responsiveness) of demand to income increases.

    Two types of Schedule 1.0 viz. Schedule Type 1 and Schedule Type 2 was canvassed in this round. Schedule Type 1 and Type 2 are similar to those of NSS 66th round.

    Reference period and schedule type: The reference period is the period of time to which the information collected relates. In NSS surveys, the reference period often varies from item to item. Data collected with different reference periods are known to exhibit certain systematic differences. Strictly speaking, therefore, comparisons should be made only among estimates based on data collected with identical reference period systems. In the 68th round - as in the 66th round -two schedule types have been drawn up. The two schedule types differonly in respect of reference period. Sample households were divided into two sets: Schedule Type 1 was canvassed in one set and Schedule Type 2 in the other.

    Schedule Type 1 uses the same reference period system as Schedule Type 1 of NSS 66th round. Schedule Type 1 requires that for certain items (Clothing, bedding, footwear, education, medical (institutional), durable goods), the same household should report data for two reference periods - 'Last 30 days' and 'Last 365 days'. Schedule Type 2 has the same reference periods as Schedule Type 2 of NSS 66th round. For Group I items (Clothing, bedding, footwear, education, medical (institutional), durable goods), the reference period used in Schedule Type 2 is 'Last 365 days'.

    As in the 66th round, items of food, pan, tobacco and intoxicants (Food-plus category) are split into 2 blocks - 5.1 and 5.2 - instead of being placed in a single block. • Block 5.1 consists of the item groups cereals, pulses, milk and milk products, sugar and salt. This block has a reference period of 30 days in both Schedule Type 1 and Schedule Type 2. • Block 5.2 consists of the other items of food, along with pan, tobacco and intoxicants. This block is assigned a reference period of 'Last 30 days' in Schedule Type 1 and a reference period of 'Last 7 days' in Schedule Type 2.

    Thus Schedule Type 1, like Schedule 1.0 of NSS 66th round, uses the 'Last 30 days' reference period for all items of food, and for pan, tobacco and intoxicants.

    Geographic coverage

    The survey covers the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sample design

    Outline of sample design: A stratified multi-stage design has been adopted for the 68th round survey. The first stage units (FSU) are the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

    Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term 'village' would include also Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of UFS blocks (2007-12) is considered as the sampling frame.

    Stratification: Within each district of a State/ UT, generally speaking, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them forms a separate basic stratum and the remaining urban areas of the district are considered as another basic stratum.

    Sub-stratification: Rural sector r: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed would be 'r/4'. The villages within a district as per frame were first arranged in ascending order of population. Then sub-strata 1 to 'r/4' have been demarcated in such a way that each sub-stratum comprised a group of villages of the arranged frame and have more or less equal population. Urban sector: If 'u' be the sample size for an urban stratum, 'u/4' number of sub-strata have been formed. In case u/4 is more than 1, implying formation of 2 or more sub-strata, this is done by first arranging the towns in ascending order of total number of households in the town as per UFS phase 2007-12 and then arranging the IV units of each town and blocks within each IV unit in ascending order of their numbers. From this arranged frame of UFS blocks of all the towns/million plus city of a stratum, 'u/4' number of sub- strata formed in such a way that each sub-stratum has more or less equal number of households as per UFS 2007-12.

    Total sample size (FSUs): 12784 FSUs have been allocated for the central sample at all-India level and 14772 FSUs have been allocated for state sample.

    Allocation of total sample to States and UTs: The total number of sample FSUs has allocated to the States and UTs in proportion to population as per census 2001 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators has been kept in view.

    Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size has been allocated between two sectors in proportion to population as per census 2001 with double weightage to urban sector. However, if such weighted allocation resulted in too high sample size for the urban sector, the allocation for bigger states like Maharashtra, Tamil Nadu, etc. was restricted to that of the rural sector. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated to each state/ UT.

    Allocation to strata/ sub-strata: Within each sector of a State/ UT, the respective sample size has been allocated to the different strata/ sub-strata in proportion to the population as per census 2001. Allocations at stratum level are adjusted to multiples of 4 with a minimum sample size of 4. Allocation for each sub-stratum is 4. Equal number of samples has been allocated among the four sub-rounds.

    Selection of FSUs: For the rural sector, from each stratum/ sub-stratum, required number of sample villages has been selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001. For the urban sector, UFS 2007-12 phase has been used for all towns and cities and FSUs have been selected from each stratum/sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR). Both rural and urban samples are to be drawn in the form of two independent sub-samples and equal number of samples have been allocated among the four sub rounds.

    Selection of hamlet-groups/ sub-blocks - important steps

    Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is first determined whether listing is to be done in the whole sample FSU or not. In case the population of the selected FSU is found to be 1200 or more, it has to be divided into a suitable number (say, D) of 'hamlet-groups' in the rural

  19. Urban population in India by state and union territory 2011

    • statista.com
    Updated Dec 31, 2015
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    Statista (2015). Urban population in India by state and union territory 2011 [Dataset]. https://www.statista.com/statistics/616121/urban-population-by-state-and-union-territory-india/
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    Dataset updated
    Dec 31, 2015
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2011
    Area covered
    India
    Description

    The statistic displays the main states and union territories with the highest number of people living in urban areas in India in 2011. In that year, the state of Maharashtra had the highest population with over 50 million people living in urban areas. The population density in India from 2004 to 2014 can be seen here.

  20. Rural and urban population in India 2018-2022

    • statista.com
    Updated Feb 27, 2024
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    Statista (2024). Rural and urban population in India 2018-2022 [Dataset]. https://www.statista.com/statistics/621507/rural-and-urban-population-india/
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    Dataset updated
    Feb 27, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    Around 908.8 million people in India lived in the rural areas in 2022, a decrease from 2021. Urban India, although far behind with over 508 million people, had a higher year-on-year growth rate during the measured time period.

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Statista (2024). Largest cities in India 2023 [Dataset]. https://www.statista.com/statistics/275378/largest-cities-in-india/
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Largest cities in India 2023

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Dataset updated
Jul 4, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
India
Description

Delhi was the largest city in terms of number of inhabitants in India in 2023.The capital city was estimated to house nearly 33 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.

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