Government Doctor: West Bengal: Average Population Served per Doctor data was reported at 10,411.000 Person in 2014. This records an increase from the previous number of 9,618.000 Person for 2013. Government Doctor: West Bengal: Average Population Served per Doctor data is updated yearly, averaging 10,411.000 Person from Dec 2004 (Median) to 2014, with 9 observations. The data reached an all-time high of 27,473.000 Person in 2012 and a record low of 8,416.000 Person in 2011. Government Doctor: West Bengal: Average Population Served per Doctor data remains active status in CEIC and is reported by Central Bureau of Health Intelligence. The data is categorized under India Premium Database’s Health Sector – Table IN.HLB002: Health Human Resources: Number of Doctors: Government.

The number of workers across the western state of West Bengal in India during financial year 2023 was over half million workers. This was an increase from the previous year. The south Asian country of India had over 14 million workers in financial year 2023.

The estimated per capita income across the eastern state of West Bengal in India stood at around *** thousand Indian rupees in the financial year 2024. There was a consistent increase in the income per capita in the state since the financial year 2012 till 2020. Sikkim recorded the highest per capita income the country.

About this dataset

Context

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

Key observations

• White: In Bengal township, the median household income for the households where the householder is White decreased by $1,558(1.74%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $89,772 in 2013 and $88,214 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Bengal township, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

West Bengal had the highest cattle population across India, at about 19 million in 2019. Uttar Pradesh ranked second that year, followed by Madhya Pradesh. Cattle population across the country grew by 0.8 percent between 2012 and 2019. Furthermore, livestock population amounted to nearly 535.8 million with cattle, buffaloes and goats making up the largest share.

Abstract

The NSS 70th round survey on land and livestock holdings (LHS) was conducted in rural areas of the country. The main objective of the survey on Land and Livestock Holdings (LHS) is to generate basic quantitative information on the agrarian structure of the country, which is relevant to land policy. The quantitative information to be collected in the land and livestock holdings survey can be categorised into the three broad aspects of land ownership holdings, operational holdings and ownership of livestock. The survey on Land and Livestock Holding has been designed to collect information on (i) particulars of land (owned, leased-out, leased-in and otherwise possessed) of the household, (ii) location of land, (iii) area, (iv) duration of possession, (v) number of lessor/lessee households, (vi) terms of lease, (vii) land use during July 2012 to December 2012/January 2013 to June 2013/whole agricultural year (July 2012 to June 2013), (viii) whether irrigated, (ix) sources of irrigation, etc. Information on number of livestock, poultry, duckery, etc., owned by the household as on the date of survey will also be collected. Besides collection of information on land and livestock, information will be collected on some household characteristics such as (i) household classification, (ii) social group, (iii) religion, (iv) whether the household operated any land on Jhum cultivation during last 365 days, etc. Some information on demographic particulars from each of the household members will also be collected such as (i) sex, (ii) age, (iii) general education level, (iv) whether associated with the household operational holding, etc.

Using the information collected in this survey, different indicators of ownership holding, operational holding, pattern in land use, detailed types of crop production/animal farming activities of the households, seasonal variation in household operational holding, ownership of livestock, poultry, duckery, etc., can be generated for the rural areas of the country.

These statistical indicators are required for planning, policy formulation and decision making at various levels within the government and outside. The results of the survey will be of use to the Department of Agriculture & Cooperation, Department of Animal Husbandry, Dairying & Fisheries, National Accounts Division, etc. These will also be used by various users, researchers and policy makers.

Geographic coverage

The survey covered the rural area of the whole of the Indian Union.

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage design has been adopted for the 70th round survey. The first stage units (FSU) are the 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 updated by excluding the villages urbanised and including the towns de-urbanised after 2001 census (henceforth the term 'village' would mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the latest updated list of UFS blocks (2007-12) is considered as the sampling frame.

Stratification: (a)Stratum has been formed at district level. 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 all the urban areas of the district. However, within the urban areas of a district, if there were one or more towns with population 10 lakhs or more as per population census 2011 in a district, each of them formed a separate basic stratum and the remaining urban areas of the district was considered as another basic stratum.

(b)However, a special stratum in the rural sector only was formed at State/UT level before district- strata were formed in case of each of the following 20 States/UTs: Andaman & Nicobar Islands, Andhra Pradesh, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Jharkhand, Karnataka, Lakshadweep, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh and West Bengal. This stratum will comprise all the villages of the State with population less than 50 as per census 2001.

(c)In case of rural sectors of Nagaland one special stratum has been formed within the State consisting of all the interior and inaccessible villages. Similarly, for Andaman & Nicobar Islands, one more special stratum has been formed within the UT consisting of all inaccessible villages. Thus for Andaman & Nicobar Islands, two special strata have been formed at the UT level: (i)special stratum 1 comprising all the interior and inaccessible villages (ii)special stratum 2 containing all the villages, other than those in special stratum 1, having population less than 50 as per census 2001.

Sub-stratification:

Rural sector: Different sub-stratifications are done for 'hilly' States and other States. Ten (10) States are considered as hilly States. They are: Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Meghalaya, Tripura, Mizoram, Manipur, Nagaland and Arunachal Pradesh.

(a) sub-stratification for hilly States: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed was '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 comprised a group of villages of the arranged frame and have more or less equal population.

(b) sub-stratification for other States (non-hilly States except Kerala): The villages within a district as per frame were first arranged in ascending order of proportion of irrigated area in the cultivated area of the village. Then sub-strata 1 to 'r/2' 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 cultivated area. The information on irrigated area and cultivated area was obtained from the village directory of census 2001.

(c) sub-stratification for Kerala: Although Kerala is a non-hilly State but because of non-availability of information on irrigation at FSU (Panchayat Ward) level, sub-stratification by proportion of irrigated area was not possible. Hence the procedure for sub-stratification was same as that of hilly States in case of Kerala.

Urban sector: There was no sub-stratification for the strata of million plus cities. For other strata, each district was divided into 2 sub-strata as follows:

 sub-stratum 1: all towns of the district with population less than 50000 as per census 2011 
 sub-stratum 2: remaining non-million plus towns of the district

Total sample size (FSUs): 8042 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 8998 FSUs allocated for all-India.

Allocation of total sample to States and UTs: The total number of sample FSUs have been allocated to the States and UTs in proportion to population as per census 2011 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators as well as comparability with previous round of survey on the same subjects 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 2011 with double 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 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated to each state/ UT.

Allocation to strata: Within each sector of a State/ UT, the respective sample size has been allocated to the different strata in proportion to the population as per census 2011. Allocations at stratum level are adjusted to multiples of 2 with a minimum sample size of 2.

For special stratum formed in the rural areas of 20 States/UTs, 2 FSUs were allocated to each.

For special stratum 1 in the rural areas of Nagaland and Andaman & Nicobar Islands, 4 and 2 FSUs were allocated respectively.

Allocation to sub-strata: Rural: Allocation is 2 for each sub-stratum in rural. Urban: Stratum allocations have been distributed among the two sub-strata in proportion to the number of FSUs in the sub-strata. Minimum allocation for each sub-stratum is 2

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Broad structure of the Schedule for collection of information in visit 1 and visit 2 are given below:

Block 0: descriptive identification of sample household Block 1: identification of sample household Block 2: particulars of field operation Block 3: household characteristics (only in visit 1) Block 4: demographic and other particulars of household members (only in visit 1) Block 5: particulars of land of the household and its operation during July 2012 to December 2012/January

Abstract

The objectives of the debt and investment survey remain the same as those of the earlier surveys, namely, to obtain quantitative information on the stock of assets, incidence of indebtedness, capital formation and other indicators or rural/urban economy which will be of value in developing the credit structure in particular, and also for obtaining other allied information required in the field of planning and development. Further, since the survey will be of the kind of a repeat survey of that of the NSS 59th round, it is considered necessary to plan the survey in such a way as to ensure, as far as practicable, comparability with the estimates of the various characteristics generated from the earlier rounds. The survey period of the 70th round was from January to December 2013. This survey covers the whole of the Indian Union. Each sample FSU is being visited twice during this round in visit 1 and visit 2. Since the workload of the first visit (i.e. visit 1) is more, the first visit continues till the end of July 2013. Thus, period of the first visit is January - July 2013 and that of the second visit (i.e. visit 2) is August - December 2013. Broadly, the following information will be collected in this round from each household: (i) the assets of the household as on 30th June 2012, classified into (a) physical assets and (b) financial assets (ii) the liabilities of the household as on 30th June 2012 in visit 1 and as on 30th June 2013 in visit 2 (iii) the amount of capital expenditure incurred by the household during July 2012 - June 2013 on (a) residential plots, houses or buildings, (b) farm business, and (c) non-farm business.

Geographic coverage

In this round all the States and Union Territories except Andaman & Nicobar Islands, Chandigarh, Dadra & Nagar Haveli and Lakshadweep are participating.

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

1. Sample Design

3.1 Outline of sample design: A stratified multi-stage design has been adopted for the 70th round survey. The first stage units (FSU) are the 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.

3.2 Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages updated by excluding the villages urbanised and including the towns de-urbanised after 2001 census (henceforth the term 'village' would mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the latest updated list of UFS blocks (2007-12) is considered as the sampling frame.

3.3 Stratification:

(a) Stratum has been formed at district level. 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 all the urban areas of the district. However, within the urban areas of a district, if there were one or more towns with population 10 lakhs or more as per population census 2011 in a district, each of them formed a separate basic stratum and the remaining urban areas of the district was considered as another basic stratum.

(b) However, a special stratum in the rural sector only was formed at State/UT level before district- strata were formed in case of each of the following 20 States/UTs: Andaman & Nicobar Islands, Andhra Pradesh, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Jharkhand, Karnataka, Lakshadweep, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh and West Bengal. This stratum will comprise all the villages of the State with population less than 50 as per census 2001.

(c) In case of rural sectors of Nagaland one special stratum has been formed within the State consisting of all the interior and inaccessible villages. Similarly, for Andaman & Nicobar Islands, one more special stratum has been formed within the UT consisting of all inaccessible villages. Thus for Andaman & Nicobar Islands, two special strata have been formed at the UT level:

(i) special stratum 1 comprising all the interior and inaccessible villages (ii) special stratum 2 containing all the villages, other than those in special stratum 1, having population less than 50 as per census 2001.

3.4 Sub-stratification:

Rural sector: Different sub-stratifications are done for 'hilly' States and other States. Ten (10) States are considered as hilly States. They are: Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Meghalaya, Tripura, Mizoram, Manipur, Nagaland and Arunachal Pradesh.

(a) sub-stratification for hilly States: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed was '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 comprised a group of villages of the arranged frame and have more or less equal population.

(b) sub-stratification for other States (non-hilly States except Kerala): The villages within a district as per frame were first arranged in ascending order of proportion of irrigated area in the cultivated area of the village. Then sub-strata 1 to 'r/2' 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 cultivated area. The information on irrigated area and cultivated area was obtained from the village directory of census 2001.

(c) sub-stratification for Kerala: Although Kerala is a non-hilly State but because of non-availability of information on irrigation at FSU (Panchayat Ward) level, sub-stratification by proportion of irrigated area was not possible. Hence the procedure for sub-stratification was same as that of hilly States in case of Kerala.

Urban sector: There was no sub-stratification for the strata of million plus cities. For other strata, each district was divided into 2 sub-strata as follows:

 sub-stratum 1: all towns of the district with population less than 50000 as per census 2011 
 sub-stratum 2: remaining non-million plus towns of the district

3.5 Total sample size (FSUs): 8042 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 8998 FSUs allocated for all-India. State wise allocation of sample FSUs is given in Table 1.

3.6 Allocation of total sample to States and UTs: The total number of sample FSUs have been allocated to the States and UTs in proportion to population as per census 2011 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators as well as comparability with previous round of survey on the same subjects has been kept in view.

3.7 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 2011 with double 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 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated to each state/ UT.

3.8 Allocation to strata: Within each sector of a State/ UT, the respective sample size has been allocated to the different strata in proportion to the population as per census 2011. Allocations at stratum level are adjusted to multiples of 2 with a minimum sample size of 2.

For special stratum formed in the rural areas of 20 States/UTs, as discussed in para 3.3 (b), 2 FSUs were allocated to each.

For special stratum 1 in the rural areas of Nagaland and Andaman & Nicobar Islands, 4 and 2 FSUs were allocated respectively.

3.9 Allocation to sub-strata:

3.9.1 Rural: Allocation is 2 for each sub-stratum in rural.

3.9.2 Urban: Stratum allocations have been distributed among the two sub-strata in proportion to the number of FSUs in the sub-strata. Minimum allocation for each sub-stratum is 2.

3.10 Selection of FSUs:

For the rural sector, from each stratum x sub-stratum, required number of sample villages has been selected by Simple Random Sampling Without Replacement (SRSWOR).

For the urban sector, FSUs have been selected by using Simple Random Sampling Without Replacement (SRSWOR) from each stratum x sub-stratum.

Both rural and urban samples were drawn in the form of two independent sub-samples and equal number of samples has been allocated among the two sub rounds.

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

3.11.1 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 approximate present population of the selected FSU is found to be 1200 or more, it is divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector by more or less equalising the population as stated below.

approximate present population of the sample FSU no. of hg's/sb's to be formed

less than 1200 (no hamlet-groups/sub-blocks) 1
1200 to 1799 3
1800 to

Rajasthan had the highest goat population across India, at about 20.4 million in 2019. West Bengal ranked second that year, followed by Uttar Pradesh. Goat population across the country grew by over ten percent between 2012 and 2019. Furthermore, livestock population amounted to nearly 535.8 million with cattle, buffaloes and goats making up the largest share.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.