The statistic shows the average number of residents living in India's households in 2012, by state and union territory. In that year, Punjab and Arunachal Pradesh had an average of **** people living in a household, while the lowest average size was in Tamil Nadu with *** people per household.

In 2019, the average household size of Hindus in Asia-Pacific was *** people per household. In comparison, Hindus in sub-Saharan Africa had the smallest average household size, at *** people per household. The majority of Hindus live in India.

Most households in India between 2019 and 2021 had between ***** and **** people. The number of ****-people households accounted for over ** percent during the survey period. Interestingly, about **** percent reported **** or more people in one household. Rural areas had a higher share of households with **** or more members.

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/.

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

In 2011, the average slum household in India had *** people. This number was a decrease from 2001. The government defines slums as residential areas with poorly built households. These are most often unhygienic and unfit for human habitation because of dilapidation, overcrowding, lack of sanitation, water and infrastructure.

In the financial year 2021, the number of super-rich households earning more than ** million Indian rupees went up to **** million from **** million in the financial year 2016. This was an annual growth of **** percent. The number is expected to grow to over **** million in the financial year 2031 and ** million households in the financial year 2047. This will be the fastest growth across all income categories. On the other hand, destitute classified Indian households with earnings of less than *** thousand annually decreased only marginally to ***** million in financial year 2021 from **** million in 2016. However, it is estimated that the number of destitute households will fall to just *** million by the financial year 2047.

BackgroundIn India, acute respiratory infections (ARIs) are a leading cause of mortality in children under 5 years. Mapping the hotspots of ARIs and the associated risk factors can help understand their association at the district level across India.MethodsData on ARIs in children under 5 years and household variables (unclean fuel, improved sanitation, mean maternal BMI, mean household size, mean number of children, median months of breastfeeding the children, percentage of poor households, diarrhea in children, low birth weight, tobacco use, and immunization status of children) were obtained from the National Family Health Survey-4. Surface and ground-monitored PM2.5 and PM10 datasets were collected from the Global Estimates and National Ambient Air Quality Monitoring Programme. Population density and illiteracy data were extracted from the Census of India. The geographic information system was used for mapping, and ARI hotspots were identified using the Getis-Ord Gi* spatial statistic. The quasi-Poisson regression model was used to estimate the association between ARI and household, children, maternal, environmental, and demographic factors.ResultsAcute respiratory infections hotspots were predominantly seen in the north Indian states/UTs of Uttar Pradesh, Bihar, Delhi, Haryana, Punjab, and Chandigarh, and also in the border districts of Uttarakhand, Himachal Pradesh, and Jammu and Kashmir. There is a substantial overlap among PM2.5, PM10, population density, tobacco smoking, and unclean fuel use with hotspots of ARI. The quasi-Poisson regression analysis showed that PM2.5, illiteracy levels, diarrhea in children, and maternal body mass index were associated with ARI.ConclusionTo decrease ARI in children, urgent interventions are required to reduce the levels of PM2.5 and PM10 (major environmental pollutants) in the hotspot districts. Furthermore, improving sanitation, literacy levels, using clean cooking fuel, and curbing indoor smoking may minimize the risk of ARI in children.

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.

For Leh (Ladakh) and Kargil districts of Jammu & Kashmir there is no separate sample first-stage units (FSUs) for "central sample". For these two districts, sample FSUs drawn as "state sample" will also be treated as central sample. The state directorate of economics and statistics (DES) will provide a copy of the filled-in schedules to Data Processing Division of NSSO for processing.

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 66th 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. In addition, two non-UFS towns of Leh and Kargil of Jammu & Kashmir are also treated as FSUs 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 mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available UFS blocks is considered as the sampling frame. For non-UFS towns, frame consists of the individual towns (only two towns, viz., Leh & Kargil constitute this 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, wherever 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: There is no sub-stratification in the urban sector. However, to net adequate number of child workers, for all rural strata, each stratum has been divided into 2 sub-strata as follows: sub-stratum 1: all villages with proportion of child workers (p) >2P (where P is the average proportion of child workers for the sate/ UT as per Census 2001) sub-stratum 2: remaining villages

Total sample size (FSUs): 12784 FSUs for central sample and 15132 FSUs for state sample have been allocated at all-India level. Further, data of 24 state sample FSUs of Leh and Kargil districts of J & K surveyed by DES, J & K will be included in the central 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 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 is allocated between two sectors in proportion to population as per census 2001 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 (to the extent possible) is allocated to each state/ UT separately for rural and urban areas. Further the State level allocations for both rural and urban have been adjusted marginally in a few cases to ensure that each stratum/ sub-stratum gets a minimum allocation of 4 FSUs.

Allocation to strata/ sub-strata: Within each sector of a State/ UT, the respective sample size is allocated to the different strata/ sub-strata in proportion to the population as per census 2001. Allocations at stratum/ sub-stratum level are adjusted to multiples of 4 with a minimum sample size of 4 and 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 urban sector, from each stratum FSUs have been selected by using Simple Random Sampling Without Replacement (SRSWOR). Both rural and urban samples have been drawn in the form of two independent sub-samples.

More information on sampling and estimation procedure is available in the document " Note on Sample Design and Estimation Procedure of NSS 66th Round". including information on: - Formation and selection of hamlet-groups/ sub-blocks - Listing of households - Formation of second stage strata and allocation of households - Selection of households - Estimation Procedure

Mode of data collection

Face-to-face [f2f]

Research instrument

During this round, the following schedules of enquiry were canvassed: - Schedule 0.0 : list of households
- Schedule 1.0 : consumer expenditure (Type 1 and Type 2) - Schedule 10 : employment and unemployment

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. The last two blocks, viz., Blocks 10 and 11 are to record the remarks of investigator and comments by supervisory officer(s), respectively.

Block 3 will be used for recording the household characteristics, like household size, religion, social group, land possessed, land cultivated, etc. For the rural households information will also be collected, in Block 3, on whether the household has NREG job card, whether got work in NREG works during the last 365 days, number of days got work in NREG works and mode of payment of the wages earned in NREG works. Besides, some particulars about holding of specified Post Office accounts and use of specified Postal services will also be collected in this block.

Block 3.1 is for recording particulars of indebtedness of rural labour households.

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

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. In this block information for all the workers about the location of workplace will also be collected. For the self-employed persons who are working under specifications (wholly or mainly), information will also be collected about "who provided credit/raw materials/equipments", "basis of payment" and "number of outlets of disposal". 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 particulars of the enterprises, informal employment and details of the self-employed persons in their subsidiary activity will be recorded in Block 5.2. The daily time disposition for the seven days preceding the date of survey along with the corresponding activity particulars will be recorded for each household member in Block 5.3. Besides this, the current weekly status (CWS) will be derived from the daily time disposition data and will be recorded in this block. As in the past, wage and salary earnings and mode of payment will also be collected for regular salaried/wage employees and for the casual labourers in this block. Block 6 will be used to record the responses to the probing questions to the persons who were unemployed on all the seven days of the reference week.

Blocks 7.1 and 7.2 contain the probing questions which are related to the under-utilisation of labour time and labour mobility, respectively.

For the members of the household classified as engaged in 'domestic duties' as per their usual principal status, some follow-up questions have been framed and listed in Block 8, with a view to collecting some additional information which might explain as to whether their usual attachment to domestic duties was voluntary or involuntary and also to throw light on their participation in some specified activities for family gain.

A worksheet to obtain the total monthly household consumer expenditure has been provided in Block 9.

According to Cognitive Market Research, the Global Household Refrigerators and Freezers Market Size was USD XX Billion in 2025 and is set to achieve a market size of USD XX Billion by the end of 2033 growing at a CAGR of XX% from 2025 to 2033.

North America held largest share of XX % in the year 2024 
Europe held share of XX % in the year 2024 
Asia-Pacific held significant share of XX % in the year 2024 
South America held significant share of XX % in the year 2024
Middle East and Africa held significant share of XX % in the year 2024

Market Dynamics

Household Refrigerators and Freezers

Key Drivers of Household Refrigerators and Freezers

The rise in the nuclear families is fueling the refrigerator market-

Growing nuclear families, along with rising disposable incomes and changing lifestyles, are fueling demand for domestic refrigerators and freezers, as the appliances are needed for food storage and preservation in small households. For instance, the joint family was the nucleus of Indian society — an institution that not only maintained cultural practices but also operated as an economic unit. Joint families shared labour and capital for farming work, family businesses, and child care. NFHS-5 data show the proportion of nuclear families in India increased to 58.2% during 2019–21 from 56% in 2016, while the size of the average household declined to 4.4 members from 4.6. In southern states, nuclear families already constitute almost 69% of all households. (Source- https://www.policycircle.org/) Further, For instance, The nuclear family, as per Taeube~5 accounts for 92.4% of the white and 83.5% of the non-white families in the United States of America. based on sample surveys, that approximately 6) % of families amongst Chinese farmers are of the nuclear type. Thus, the number of nuclear families are growing. The demand for the refrigerator and household freezers also increases. (Source- https://iris.who.int/bitstream/handle/) With the growing popularity of nuclear families, the demand for convenient and efficient means to store food rises, which raises demand for freezers and refrigerators. With hectic lifestyles and a love for convenience, individuals are more and more dependent on freezers and refrigerators to hold prepared foods and groceries. The market is witnessing advancements in refrigeration technology, with more energy-efficient versions, smart features, and higher capacities gaining greater popularity. The worldwide household freezers and refrigerators market is expected to continue expanding, based on factors such as increasing disposable incomes, urbanization, and shifting consumer behaviors. Rise in the number of nuclear families. Because Increased household income and educational levels tend to be linked with a higher probability of nuclear family forms, particularly in urban settings where there is a growing desire for economic independence and individual space. Mostly in united states, Canada, Germany. Thus, the increasing popularity of nuclear families, combined with increasing disposable incomes and changing lifestyles, is fueling high demand for household refrigerators and freezers. These products have become a necessity for food storage and preservation. As urbanisation and changing consumer trends reshape the world, the demand for innovative and adaptable refrigeration solutions will continue to increase.

Key Restraints of Household Refrigerators and Freezers

Higher initial outlay and issues with affordability as a hindrance to the household refrigerators and freezers market

Although innovation in smart technology, sustainability, and energy efficiency has benefited the refrigeration and freezing business significantly, one of the major constraints of advanced models is their high cost of purchase. Although consumers' interest in greener and smarter appliances is increasing, the price of these highly advanced refrigerators and freezers may prove a stumbling block to many prospective purchasers. For instance, July 2021, Smart Home Program - Technology Assessment Study and Pilot Design- models with cutting-edge technology such as smart features (touchscreens, voice controls, and Wi-Fi connectivity) or energy-saving compressors will cost more than basic, conventional models. Such high-tech refrigerators are usually several hundred or even a thousand dollars more expensive, out of budget fo...

Abstract

The second National Family Health Survey (NFHS-2), conducted in 1998-99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15-49. The NFHS-2 sample covers 99 percent of India's population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state.

IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992-93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women's autonomy, domestic violence, women's nutrition, anaemia, and salt iodization.

The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia.

SUMMARY OF FINDINGS

POPULATION CHARACTERISTICS

Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas.

The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups.

Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1.

About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6-8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6-7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6-14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6-10, 85 percent of boys attend school compared with 78 percent of girls. By age 15-17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6-17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala.

Women in India tend to marry at an early age. Thirty-four percent of women age 15-19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45-49 married before age 15 compared with 14 percent of women currently age 15-19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20-24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa.

As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women's involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women's work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60-70 percent in Manipur, Nagaland, and Arunachal Pradesh.

FERTILITY AND FAMILY PLANNING

Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7-9 percent of births in Kerala, Goa, and Tamil Nadu.

Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20-49 had their first birth before reaching age 20, and women age 15-19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young ages?both for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility.

INFANT AND CHILD MORTALITY

NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0-11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1-4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care.

HEALTH, HEALTH CARE, AND NUTRITION

Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

Data and insights on Wealth Distribution in India - share of wealth, average wealth, HNIs, wealth inequality GINI, and comparison with global peers.

India Home Appliances Market size was valued to be USD 18 Billion in the year 2024 and it is expected to reach USD 30 Billion in 2032, at a CAGR of 5.5% over the forecast period of 2026 to 2032.

Key Market Drivers

Rising Disposable Income and Middle Class: Growth The average household disposable income in India grew by approximately 8-10% annually between 2020-2023, with the middle class expected to reach 547 million people by 2025. This has directly correlated with increased spending on home appliances, particularly in Tier 2 and 3 cities.

Urbanization and Nuclear Family Structure: India's urban population is projected to reach 600 million by 2025, with over 65% of households being nuclear families. These smaller urban households typically spend 25-30% more on home appliances than joint families.

Households Debt in India increased to 42 percent of GDP in the first quarter of 2025 from 41.90 percent of GDP in the fourth quarter of 2024. This dataset provides - India Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. From 1880 until 1970, India's fertility rate was very consistent, and women of this time had an average of 5.7 to six children over the course of their lifetime. In the second half of the twentieth century, the fertility rate dropped considerably, and has continued to drop in the 2000s. This decrease in the rate of fertility follows a common correlation between quality of life and fertility, where the fertility rate decreases as the standard of living improves. In 1947, after almost a century, the Indian independence movement finally achieved its goal, and India was able to self rule. From this point onwards, Indian socio-economic improvements led to a decreased fertility rate, which is expected to fall to 2.2 in 2020.

In 2023, the total fertility rate in children per woman in India was 1.98. Between 1960 and 2023, the figure dropped by 3.94, though the decline followed an uneven course rather than a steady trajectory.

In the financial year 2024, India's household debt reached around *** billion U.S. dollars, an increase from previous year's figures. India's household debt has witnessed an upward trend in the last decade. Household debt includes consumer durables, housing and other personal loans.

In 2024, the average monthly salary was **** thousand Indian rupees in Mumbai city of India. The average monthly salary in the capital city of Delhi was around **** thousand Indian rupees. In comparison, the average monthly salary was over ** thousand Indian rupees in Madurai during the same year.

The estimated per capita income across Sikkim was the highest among Indian states at around *** thousand Indian rupees in the financial year 2024. Meanwhile, it was the lowest in the northern state of Bihar at over ** thousand rupees. India’s youngest state, Telangana stood in the fifth place. The country's average per capita income that year was an estimated *** thousand rupees. What is per capita income? Per capita income is a measure of the average income earned per person in a given area in a certain period. It is calculated by dividing the area's total income by its total population. If absolute numbers are noted, India’s per capita income doubled from the financial year 2015 to 2023. Wealth inequality However, as per economists, the increase in the per capita income of a country does not always reflect an increase in the income of the entire population. Wealth distribution in India remains highly skewed. The average income hides the disbursal and inequality in a society. Especially in a society like India where the top one percent owned over ** percent of the total wealth in 2022.