As of 2024, the Sustainable Development Goal (SDG) index score for reducing poverty (SDG 1) ranges between 39 and 92 for Indian states and union territories. Among the states, Tamil Nadu and Telangana were the front-runners with a score of 92 and 91. Among the union territories, Dadra & Nagar Haveli and Daman & Diu were the front-runner with a score of 89.

The Consumer Price Index across all groups of commodities decreased to 4.1 percent in urban India compared to 5.0 percent in rural areas during financial year 2025. CPI-based inflation remained higher in rural areas as compared to urban areas during the examined period.

The dataset contains All India Yearly Number and Percentage of Population Below Poverty Line from Handbook of Statistics on Indian Economy.

Looking back 45 years or so, progress against poverty in India has been highly uneven over time and space. It took 20 years for the national poverty rate to fall below—and stay below—its value in the early 1950s. And trend rates of poverty reduction have differed appreciably between states. This research project aimed to understand what influence economy-wide and sectoral factors have played in the evolution of poverty measures for India since the 1950s, and to draw lessons for the future.

This database contains detailed statistics on a wide range of topics in India. The data are presented at the state level and at the all-India level separately. The database uses published information to construct comprehensive series in six subject blocks. Period coverage is roughly from 1950 to 1994. The database contains 30 spreadsheets and 89 text files (ASCII) that are grouped into the six subject blocks. The formats and sizes of the 30 spreadsheets vary considerably. The list of variables included:

. Expenditures (distribution)
. National Accounts
. Prices Wages
. Population
. Rainfall

Historical dataset showing India poverty rate by year from 1977 to 2022.

The dataset contains Year and State wise Poverty Rate-Number of Persons and Percentage

Lakdawala Methodology: An older method to measure poverty in India based on minimum calorie intake (2,400 rural / 2,100 urban). It used a 30-day recall for all expenses but did not include health and education costs.

Tendulkar Methodology:A revised method that considers actual spending on food, health, education, etc. It uses a mixed recall period and provides a more realistic estimate of poverty.

Mixed Recall Period: Combines two recall periods: 30 days for regular items and 365 days for infrequent ones. This helps reduce errors and gives a better picture of total household spending.

30-Day Recall Period: Collects data based on what households spent in the last 30 days for all items. It may miss big or occasional expenses and can underestimate actual consumption.

Looking back 45 years or so, progress against poverty in India has been highly uneven over time and space. It took 20 years for the national poverty rate to fall below—and stay below—its value in the early 1950s. And trend rates of poverty reduction have differed appreciably between states. This research project aimed to understand what influence economy-wide and sectoral factors have played in the evolution of poverty measures for India since the 1950s, and to draw lessons for the future. This database contains detailed statistics on a wide range of topics in India. The data are presented at the state level and at the all-India level separately. The database uses published information to construct comprehensive series in six subject blocks. Period coverage is roughly from 1950 to 1994. The database contains 30 spreadsheets and 89 text files (ASCII) that are grouped into the six subject blocks. The formats and sizes of the 30 spreadsheets vary considerably. The list of variables included: . Expenditures (distribution) . National Accounts . Prices Wages . Population . Rainfall

Using unit data from the Indian Human Development Survey (IHDS), 2004-05, this paper estimates and decompose the multidimensional poverty dynamics in 84 natural regions of India. Multidimensional poverty is measured in the dimensions of health, knowledge, income, employment and household environment using ten indicators and Alkire-Foster methodology. The unique contributions of the paper are inclusion of a direct economic variable (consumption expenditure) to quantify the living standard dimension, decomposition of MPI across the dimensions and the indicators and provide estimates at sub-national level. Results indicate that about half of India's population are multidimensional poor with large regional variations. More than 70% of the population are multidimensional poor in the Mahanadi Basin, the southern region of Chhattisgarh and the Vindhya region of Madhya Pradesh, while it is less than 10% in the coastal regions of Maharashtra, Delhi, Goa, the mountainous region of Jammu and Kashmir, the Hills region and Plains region of Manipur, Puducherry and Sikkim. The decomposition of MPI indicates that economic dimension alone accounts for about one-third of multidimensional poverty in most of the regions of India. Based on these analyses, the authors suggest target based interventions in the poor regions to reduce poverty and inequality, and achieve the Millennium Development Goals in India.

Urban poverty rate of India plummeted by 34.45% from 20.9 % in 2009 to 13.7 % in 2011. Since the 19.18% drop in 2004, urban poverty rate sank by 46.69% in 2011. Urban poverty rate is the percentage of the urban population living below the national urban poverty line.

India IN: Poverty Headcount Ratio at $3.65 a Day: 2017 PPP: % of Population data was reported at 44.000 % in 2021. This records a decrease from the previous number of 48.200 % for 2020. India IN: Poverty Headcount Ratio at $3.65 a Day: 2017 PPP: % of Population data is updated yearly, averaging 62.000 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 89.100 % in 1977 and a record low of 44.000 % in 2021. India IN: Poverty Headcount Ratio at $3.65 a Day: 2017 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $3.65 a day is the percentage of the population living on less than $3.65 a day at 2017 international prices.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

In 2024, the Gini coefficient of wealth in India stood at 74. This was a slight decrease from previous years. The trend since 2005 shows rising inequalities among the Indian population. What is Gini coefficient of wealth? The Gini coefficient is a measure of wealth inequality. The coefficient of the Gini index ranges from 0 to 1 with 0 representing perfect equality and 1 representing perfect inequality. Wealth and income distribution and inequality can however vary greatly. In 2023, South Africa topped the list of the most unequal countries in the world in terms of income inequality. Why do economic inequalities persist in India? By the end of 2022, the richest citizens in the country owned more than 40 percent of the country’s wealth. Asia’s two richest men Mukesh Ambani and Gautam Adani are Indians. The number of high-net-worth individuals has continuously increased over the last decades. While millions of people escaped poverty in the country in the last few years, the wealth distribution between rich and poor remains skewed. Crony capitalism and the accumulation of wealth through inheritance are some of the factors behind this widening gap.

As of 2022, over 13 million children between the ages of 10 to 14 years were affected by poverty. In general, age groups from 0 to 19 years were most impacted by extreme poverty.

Poverty rate of India plummeted by 31.46% from 32.8 % in 2009 to 22.5 % in 2011. Since the 10.63% drop in 1983, poverty rate sank by 60.09% in 2011. Population below $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices.

BackgroundThough the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and MethodologyUsing unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. ResultsThe estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. ConclusionUse of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 2.010 Intl $/Day in 2011. This records an increase from the previous number of 1.610 Intl $/Day for 2004. India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 1.810 Intl $/Day from Dec 2004 (Median) to 2011, with 2 observations. The data reached an all-time high of 2.010 Intl $/Day in 2011 and a record low of 1.610 Intl $/Day in 2004. India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Graph and download economic data for Estimate of Related Children Age 5-17 in Families in Poverty for Indian River County, FL (PE5T17FL12061A647NCEN) from 1989 to 2023 about Indian River County, FL; Sebastian; 5 to 17 years; family; child; poverty; FL; persons; and USA.

India Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 2.570 % in 2017. This records a decrease from the previous number of 3.400 % for 2011. India Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 1.930 % from Dec 1995 (Median) to 2017, with 9 observations. The data reached an all-time high of 3.400 % in 2011 and a record low of 1.290 % in 2001. India Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

India Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 16.400 % in 2019. India Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 16.400 % from Dec 2019 (Median) to 2019, with 1 observations. The data reached an all-time high of 16.400 % in 2019 and a record low of 16.400 % in 2019. India Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

Poverty rate at national poverty line of India plummeted by 26.51% from 29.8 % in 2009 to 21.9 % in 2011. Since the 19.89% drop in 2009, poverty rate at national poverty line sank by 26.51% in 2011. National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys.