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The Great Indian Poverty Debate, 2.0

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TL;DR: Has the Modi government accelerated or decelerated poverty reduction? It’s hard to know, as India has effectively stopped measuring poverty. A new World Bank paper using private-sector survey data finds the share of people living below $1.90 per day has been falling, but is higher than we thought, at about 10 percent. A rival paper from India's representative at the IMF says India has joined China in (almost) fully eradicating extreme poverty. Both estimates seem optimistic given other economic indicators.

For the past decade, India hasn’t released any official poverty numbers

In the early 2000s, economists engaged in a heated debate about how much India's 1990 liberalization had reduced poverty. Christening it The Great Indian Poverty Debate , Nobel Laureate Angus Deaton and Valerie Kozel noted "the various claims have often been frankly political, but there are also many important statistical issues." Twenty years later, history repeats.

The underlying question this time is whether Narendra Modi, who assumed office in 2014, has been good for poverty reduction. From a technical perspective, this debate is interesting because the data are so bad. If the data were good, there'd be no need for fancy imputations. But because the integrity of India’s statistical system has come into question over recent years, facts are up for grabs.

Official poverty measurement essentially stopped in 2011/12. There are hints of bad news behind that pause. Leaked data from the 2017/18 National Sample Survey showed a startling 3.7 percent decline in real consumption over six years, and the survey was never released. Though in fairness, as discussed on this blog in the past, those preliminary numbers seemed implausibly dire.

In the absence of official survey data, two new papers released this month offer creative solutions to fill in the gaps, and reach starkly different conclusions about what might be happening to poverty.

A new paper by World Bank researchers estimates extreme poverty in India is higher than previously thought at 10.2 percent in 2019

Sutirtha Roy and Roy van der Weide use data from the Consumer Pyramid Household Survey (CPHS) run by the Centre for Monitoring the Indian Economy to come up with a new estimate of Indian poverty. That's no small feat. The official data stop in 2011 and the CPHS only started in 2014, its sample appears to undercount poor households , and even small differences in how consumption questions are asked can make a big difference. So Roy and van der Weide spend many pages explaining how they reweight the CPHS data to make it comparable to the NSS series⁠—impressively painstaking work that I can't really do justice to here.

The end result though is cautiously optimistic. The title really lives up to the frequent exhortation to researchers to "just say what you found": Poverty in India Has Declined over the Last Decade But Not As Much As Previously Thought . They make four basic claims:

Extreme poverty fell 12.3 percentage points from 2011 to 2019 using the World Bank’s $1.90 per day line in purchasing-power parity terms.
Poverty stands at 10.2 percent in 2019, considerably higher than earlier projections based on consumption growth observed in national accounts.
Urban poverty rose by 2 percentage points during the 2016 demonetization, and rural poverty reduction stalled by 2019, when the economy slowed.
Inequality has stopped rising since 2011.

The basic story can be seen in the figure below: still good news, but less so than if you just relied on national accounts.

Figure 1. Indian poverty (<$1.90 PPP) since the official data series stopped

Source: Roy & van der Weide 2022, Figure 17

There were good ex ante reasons to think the projection based on the national accounts system (NAS) shown by the dotted line in Figure 1 was too optimistic⁠—more on that below. But consumption growth in the CPHS survey also looks surprisingly high in the latter years, especially 2019-20. That year the index of industrial production for consumer goods registered an absolute decline of 3.8 percent (even more in per capita terms), real rural wages declined, and real urban wages grew less than 2 percent—meanwhile the CPHS showed growth in real per capita consumption of 6.2 percent.

But if the Roy and van der Weide estimate seems mildly optimistic, fasten your seatbelts...

An IMF working paper released the same week says India had eradicated extreme poverty by 2019, and held it near zero through the pandemic

At the same time the World Bank released the Roy and van der Weide estimates, the IMF published an alternative estimate coauthored by Surjit Bhalla , the Indian government's representative at the IMF and a well-published economist who is a veteran of the first great Indian poverty debate. In their paper, Bhalla and coauthors Karan Bhasin and Arvind Virmani eschew new survey data entirely. Instead, they start from the last official 2011/12 survey and shift the distribution in line with the growth of consumption in the national accounts, and then add in explicit allowance for government food subsidies. The conclude that:

India has essentially eliminated extreme poverty. They estimate the proportion of the population below $1.90 in PPP terms at just 0.8 percent before the pandemic.
The pandemic didn't increase poverty. Rather, "food transfers were instrumental in ensuring that it remained at that low [0.8 percent] level in pandemic year 2020.”
Inequality has fallen to the lowest level since 1993/94, with a Gini after transfers of 0.29.

Note that the 0.8 percent poverty rate that Bhalla et al cite here is using a different definition of the underlying consumption aggregate than the one used by the World Bank above (based on the NSS's MMRP series instead of the URP series, for those who follow this stuff). In more apples-to-apples terms, their (URP) number is 1.9 percent—still very low.

Figure 2. An alternative view of Indian poverty, with and without adjusting for an increase in transfers from the Public Distribution System

Source: Bhalla, Bhasin, and Virmani 2022, Figure 1

The novel and interesting claim in the Bhalla et al paper is that previous estimates have overestimated poverty because they rely only on survey measures of actual expenditure on food items, implicitly omitting the government subsidy embodied in India's massive Public Distribution System (PDS). Using administrative data on PDS and various assumptions, Bhalla et al get a significantly lower poverty rate.

It's unclear (to me) how the paper has dealt with leakage from the PDS system, and errors of inclusion and exclusion which we know are rampant. But a recent survey from my CGD colleagues found that the ration system held up quite well during the pandemic. So the question Bhalla et al raise about how much Modi's new welfarist policies may have reduced national poverty is an interesting and important one, even if their impact is at most a couple of percentage points.

[A technical aside: while interesting, it’s not clear that it’s strictly valid to add in the subsidy value to Indian consumption for calculating globally comparable poverty rates using the World Bank’s $1.90 PPP line, unless one does the same for other countries, who also have various food and energy subsidies.]

The deeper challenge with the Bhalla et al "zero poverty" calculation is its reliance on official national accounts data, which various pieces of evidence suggest will exaggerate true poverty reduction.

The optimistic view on Indian poverty requires that GDP growth was exaggerated before 2011, and hasn't been since — two claims open to debate

There's been a lot of ink spilled about India's national accounts in the last several years, so it's worth distinguishing two different issues.

First, my CGD colleague Arvind Subramanian has made the case (and here ) that the government began, inadvertently at first but systematically, overstating GDP growth after 2011 (pre-Modi). And earlier World Bank estimates for India have included that possibility in their poverty scenarios, though neither Roy and van der Weide nor Bhalla et al do so here. If Subramanian is right, then poverty may be significantly higher than both sets of national accounts projections imply. Indeed, Subramanian’s caution on the recent GDP figures would point in the same direction as Roy and van der Weide’s preferred survey-based poverty estimates, at least through 2017.

Second, in the absence of new survey data, Bhalla et al extrapolate survey consumption from 2011 by assuming nominal consumption growth in national accounts passes through to growth in the survey mean, one for one. They show this was roughly true in India’s most recent pre-2011 survey rounds. But a large literature, starting with Ravallion (2003) , shows this doesn’t hold in general. And more recent World Bank research concludes the most plausible rate of pass through for India from real consumption in national accounts to surveys is 0.67. That’s why Roy and van der Weide get a much higher poverty rate than Bhalla et al, even when the former use the same national accounts data.

To compound matters, the historical national accounts data underlying Bhalla and coauthors’ estimates are subject to their own heated debate—totally separate from Subramanian’s critiques of the newer national accounts. In 2018, the National Statistical Commission recommended a backward revision to the GDP series that would have raised the growth rate from 2004-05 to 2011-12 a fraction of a percentage point. But a few months later, the government’s internal think tank, NITI Aayog, decided to go the opposite direction, and published a new backcast GDP series revised in the opposite direction , implying growth in GDP and consumption before 2011 was more than a full percentage point lower . (Critics contended that lowering historical growth helped make the current government look good by comparison.) One side-effect of the downward revision is that it made national accounts and survey data look more consistent, yielding Bhalla et al’s finding of 100 percent pass through. If instead one stuck with the original pre-2011 national accounts, or even more so the National Statistical Commission’s recommendation, you’d have to conclude 100 percent pass through is too high, and hence the implied poverty rate in 2019 is too low.

In sum, there is unlikely to be any resolution to this debate any time soon, but reliance on national accounts only kicks the ball into even more fraught and politicized territory. As it stands now, we have a wide range of estimates for poverty changes since the last (accepted) estimate of 22.5 percent for 2011/12: from an increase (unreleased NSS, 2017/18) to a near-elimination by 2019 (Bhalla and coauthors) with the Roy and van der Weide 2019 estimate falling in-between at about 10 percent.

Until the integrity of the official household surveys is restored, any judgment on the Modi government’s efforts to reduce poverty appears tentative at best, and the great Indian poverty debate will go on.

Thanks to Surjit Bhalla, Alan Gelb, Christoph Lakner, Maria Ana Lugo, Anit Mukherjee, Sutirtha Roy, Arvind Subramanian, and Roy van der Weide for helpful comments and clarifications. Any conclusions (or errors) here are mine alone.

CGD blog posts reflect the views of the authors, drawing on prior research and experience in their areas of expertise. CGD is a nonpartisan, independent organization and does not take institutional positions.

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Multidimensional poverty in India: a study on regional disparities

Published: 04 August 2021
Volume 87 , pages 3987–4006, ( 2022 )

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Pinaki Das 1 ,
Sudeshna Ghosh ORCID: orcid.org/0000-0002-2026-1676 2 &
Bibek Paria 1

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The primary objective of this study is to investigate the regional disparities of multidimensional poverty (MPI) in the context of India. This study to our knowledge is the first of its kind which examined MPI disparity at a regional level. The study has classified the geographic area of India into six regions: Northern, Eastern, North Eastern, Central, Western and Southern region. Further, we explore MPI across population sub-groups within a region. Using the latest available household data from the National Family and Health Survey over 2005–2006 and 2015–2016 we explored how at the regional level multidimensional poverty changed within a decade. The paper estimates MPI in India at a regional level following the methodology of Alkire and Foster (2011). The Eastern rural region has the highest MPI 0.43 (2005–2006) and 0.21 (2015–2016). The lowest MPI is in the Northern region 0.14 and 0.03 respectively. The Northern region further has lowest MPI across all social sub-groups. The results also demonstrate regional concentration of MPI particularly in the Central and Eastern regions. A major disquieting feature is that the regional variation in MPI across the Eastern and the Northern region increased by four times in 2015–2016 compared to the earlier period. The study further obtains that though multidimensional poverty has reduced significantly over the decade the decline is regressive. It can be traced to the nature of regressivity in the decline in the different deprivation indicators. The present study suggests that India must endeavour the process of balanced regional development.

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Das, P., Ghosh, S. & Paria, B. Multidimensional poverty in India: a study on regional disparities. GeoJournal 87 , 3987–4006 (2022). https://doi.org/10.1007/s10708-021-10483-6

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Patrons of the Poor: Caste Politics and Policymaking in India

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Introduction: Analysing Poverty in India

Published: April 2011
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Poverty in India has proven to be inflexible ever since the country gained its independence more than fifty years ago, prompting the question of what the role of the state or public policy is in reducing poverty in India. This introductory chapter examines the central role of politics in helping to reduce poverty levels in India, as well as the theoretical background of an analysis on poverty. This includes the regime type, which is considered as the ultimate unit of analysis. The chapter discusses class politics, public policy, and caste dominance, and provides a working definition of ‘poverty’. In the latter portion of the chapter, there is a discussion on the state politics and empirical evidence of the poverty levels in two Indian states, Karnataka and Tamil Nadu. The chapter ends with a discussion of the research questions, theoretical implications, and original contribution of the book.

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Poverty and Inequality in India: An Exploratory Analysis

Department of Economic History
Gokhale Institute of Politics and Economics

Research output : Contribution to journal › Article › peer-review

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35-125-1-PB Final published version, 127 KB Licence: CC BY

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Poverty Business & Economics 100%
India Business & Economics 81%
Social Deprivation Business & Economics 72%
State Intervention Business & Economics 55%
Central Planning Business & Economics 55%
Economic Reform Business & Economics 55%
Economic Liberalization Business & Economics 53%
Deprivation Business & Economics 52%

T1 - Poverty and Inequality in India

T2 - An Exploratory Analysis

AU - Hatti, Neelambar

AU - Hari, K. S.

PY - 2015/12

Y1 - 2015/12

N2 - India is a country characterized by multi-layered diversity and cultural heterogeneity where different types of inequalities and poverty have always been a fact of life. Since independence in 1947, she followed a development policy based on interventionist central planning and import substitution with the objective of reducing inequality and poverty. Policymakers adopted a middle path in which income inequality was tolerated, provided it was not ‘excessive’ and led to a higher rate of growth. From the mid-1980s, the Indian government gradually adopted market-oriented economic reforms. The pace accelerated during the early 1990s with the adoption of neo-liberal reforms programmes, marking a period of intensive economic liberalization. The focus changed from state intervention for more equitable distribution towards liberalization, privatization and globalization. During the past two decades, India has made rapid economic progress resulting in an expanding middle class with unprecedented access to goods and opportunities. Yet, it is not only that the new income generated by economic growth has been very unequally shared, but also the resources newly created have been inadequately utilized to alleviate the enormous social and economic deprivation of a majority of the society. This paper analyses the nature and causes of inequality and poverty in India.

AB - India is a country characterized by multi-layered diversity and cultural heterogeneity where different types of inequalities and poverty have always been a fact of life. Since independence in 1947, she followed a development policy based on interventionist central planning and import substitution with the objective of reducing inequality and poverty. Policymakers adopted a middle path in which income inequality was tolerated, provided it was not ‘excessive’ and led to a higher rate of growth. From the mid-1980s, the Indian government gradually adopted market-oriented economic reforms. The pace accelerated during the early 1990s with the adoption of neo-liberal reforms programmes, marking a period of intensive economic liberalization. The focus changed from state intervention for more equitable distribution towards liberalization, privatization and globalization. During the past two decades, India has made rapid economic progress resulting in an expanding middle class with unprecedented access to goods and opportunities. Yet, it is not only that the new income generated by economic growth has been very unequally shared, but also the resources newly created have been inadequately utilized to alleviate the enormous social and economic deprivation of a majority of the society. This paper analyses the nature and causes of inequality and poverty in India.

KW - Poverty

KW - Inequality

KW - poverty

KW - inequality

M3 - Article

SN - 2454-2806

JO - Social Science Spectrum

JF - Social Science Spectrum

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Measuring Trends in Multidimensional Poverty

This article questions the methodology adopted in NITI Aayog’s discussion paper on the progress of multidimensional poverty in India between 2005–06 and 2022–23. It highlights some of the limitations of the concept of multidimensional poverty and cautions against measuring the multidimensional poverty index through interpolation and extrapolation of past trends. It shows that the rate of poverty decline has actually declined after 2014–15. It is argued that instead of jumping to hasty conclusions based on a questionable statistical exercise, we should wait for the actual data on different indicators of MPI whenever these become available.

The NITI Aayog has come out with a discussion paper on the progress of multidimensional poverty in India between 2005–06 and 2022–23 written by Ramesh Chand and Rajesh Suri (NITI Aayog 2023). It needs to be noted that it is only a discussion paper and not an official document of the NITI Aayog. The aim of a discussion paper is to get feedback from other experts. The paper, using a questionable methodology for interpolating and extrapolating, comes to the conclusion that multidimensional poverty has declined from 29% in 2013–14 to 11% in 2022–23, with about 248 million people escaping poverty in the nine years of the present rule. One wonders as to why such an exercise was undertaken when no new data on the variables was available. The aim seems to be just to show that the performance of the present government in the reduction of poverty was better than that of the previous government. Amitabh Kundu and K S James (2024) have defended the assumptions made in the discussion paper, though they accept that using different assumptions, one can arrive at different estimates of MPI.

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Poverty and inequality in India - statistics & facts

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Contribution of deprivation to overall multidimensional poverty in India 2021

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Multidimensionally poor and deprived population in housing in India 2006-2021

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Youth development in India: does poverty matter?

Bijaya kumar malik.

Department of Education in Social Sciences, National Council of Educational Research and Training, New Delhi, India

This paper explores the differentials in youth development patterns determined by the economic condition of the household in India. The wealth index is used to glean youth development differentials in the different economic categories of the household. The findings suggest that youth from the bottom 20 per cent (poorest) of households are deprived in education, employment, labour force and are not working currently compared to youth from the middle and rich households. The states differ in youth development patterns (employment, appropriate education, skill development and awareness about health). There are more working youth among poor households than among rich households in India. Female youth are more disadvantaged compared to male youth and it is the same with the rural–urban distribution of youth. This paper concludes that the various economic categories/wealth index (poorest, poorer, middle, richer and richest) directly determine the pattern of youth development in India.

India has one of the highest adolescent (253 million) and youth populations in the world. The Census of India ( 2011 ) has highlighted the profile and status of the adolescent and youth population, which constitutes a critical segment of the total population of India. Socio-political, economic and demographic developments depend on them. The transition from education and training to economic activity marks an important phase in the lives of youth, who are the productive workforce of the country. The huge unemployment among youth due to lack of skills and poverty is a long term challenge for India.

In 2010, it was estimated that the population of the world was 6.91 billion and that adolescent population (10–19 years) constituted 1.19 billion and youth (15–24 years) 1.22 billion, which together accounted for 26.3 per cent of the total population of the world (World Population Prospects: the 2012 Revision, June 2013). In India, the adolescent population is 253 million and the youth population is 231.9 million, which constitute 20.9 per cent and 19.2 per cent of the total population respectively and both adolescent and youth population comprise 40.1 per cent of the total population of India (Census of India 2011 ). Compared to the 2001 Census, the percentage of adolescents has declined, while that of youth has increased due to a decline in the level of fertility. There was an addition of nearly 181.9 million to India’s total population during the 2001–2011 Census and youth population added 41.8 million to its population segment. The youth population of India is so huge that it is equivalent to the total population of eighteen countries in western Asia according to United Nations estimates (World Population Prospects: The 2012 Revision 2013 ).

Youth is defined as those persons in the age group 15–24 years by the United Nations, though the age range for youth may vary in different countries due to different contexts and needs of youth. During this transitional phase, physical, educational, psychological, social and economic changes occur in their lives. The India National Youth Policy (NYP) covers all youth in the age group 13–35 years, which is divided into two groups, that is, 13–19 years and 20–35 years (National Youth Policy 2003 ). The recent National Youth Policy has defined youth as those in the age group 15–29 years, who comprise 27.5 per cent of the population. Youth is a more fluid category than a fixed age-group. ‘Youth’ is often indicated as a person between the age where she/he leaves compulsory education, and the age at which she/he finds her/his first employment (National Youth Policy 2014 ). The study, Youth in India: Situation and Needs , considered youth as those in the age group 15–24 years and this paper follows this definition.

Every year, the Government of India allotted Rs. 2710/-per youth per year for development in terms of employment, appropriate education, skill development and awareness about health (Union Budget, 2011–2012). State governments, institutions, other stakeholders and Non-Governmental Organizations (NGOs) also supported the development of youth, towards making them a productive workforce.

In 2000, the United Nations Millennium Development Goals (MDGs) committed to combat HIV/AIDS, malaria and other diseases under Goal 6: target 19, that is, equipping those in the age group, 15–24 years with comprehensive and correct knowledge of HIV and AIDS and evolving a global partnership for development under Goal-8: target-45, that is, unemployment rate of young people aged 15–24 by sex by 2015 for all countries Youth seemed to have heard about these issues, but lacked comprehensive knowledge.

Importance of youth for the demographic dividend in the Indian context

In many countries, demographic transition is achieved after the large segment of adolescent and youth population joins the total population. This happens only when there is a transition of its population from a high to a low situation for both mortality and fertility over a particular period, which also known as the demographic window of opportunity. Demographic dividend can be achieved when economic growth accelerates. This occurs when the working age group population, having acquired technical and vocational skills, engage themselves in economic activities. The implementation of national policies over a period of time supports the process. This significant shifting of age structure in the Indian population, can increase economic participation and reduce dependency, which will support economic growth. Many demographers and economists have forecast that India will reap the demographic dividend through its working population, which has a huge latent potential and productivity. Literacy rate among youth increased from 36 per cent in 1962 to 86.1 per cent in 2011. There is some difference between male literacy (90 %) and female literacy (81.8 %), and that of rural youth (83.7 %) and urban youth (91.4 %) youth according to Census, 2011.

Review of literature

Various research studies have shown how socioeconomic factors determine the youth development pattern in the Indian context. There is evidence that the young (16–24 years) are particularly more prone towards the negative effects of recession, which create a spell of unemployment (Bell and Blanchflower 2010 ). Global recession creates a huge volume of temporary employment among them (Higgins and Niall’ 2012 ). Low literacy rate and health problems among female youth are obstacles for the development of youth in India (Dreze et al. 2011 ).

Rationale for the study

The youth population in any country is dynamic and important for its long run development. The latent power and demographic shift of the Indian youth population can improve our economy. In 2014, the Government of India formulated a National Youth Policy covering eleven priority areas— Education, Employment and Skill Development, Entrepreneurship, Health and Healthy Lifestyle, Sports, Promotion of Social Values, Community Engagement, Participation in Politics and Governance, Youth Engagement, Inclusion, and Social Justice —which provides youth a strong road map for realizing the proposed goals during the next 5 years with an appropriate framework. NYP ( 2014 ) aims to empower Indian youth to utilize their full potential. According to this policy, youth in the age group, 15–29 years comprises 27.5 per cent of the population. This significant segment of population can increase its labour participation and productivity to better our economy. It is estimated to contribute about 34 per cent of the Gross National Income (NYP 2014 ).

The Census of India ( 2011 ) has released a number of indicators on youth including other age groups, literacy, work status, total population and age wise population. Some important socioeconomic and demographic indicators are to be released by the Census, which will help researchers and academicians to investigate youth development in detail for formulating national plans and policies. Socioeconomic and demographic variables are not available from the Census of India currently; despite these constraints, this research paper makes an effort to study how various factors especially poverty/wealth index is related to the youth development pattern (employment, appropriate education, skill development and awareness about health) in India by using data from the demographic survey, Youth in India: Situation and Needs: 2006 – 2007 conducted by IIPS, Mumbai and Population Council, which covered key areas like education, unemployment, work participation rate and other demographic variables. In this paper, wealth index and other related variables have been used as background variables to know the differentials of youth engagement and their developmental pattern in India.

Research questions

Does poverty determine the pattern of youth development (employment, appropriate education, skill development and awareness about health) in India?
What are the social, cultural and other barriers to youth development in India?
What kind of national policy framework will provide more support and empower youth in India?

The broad objective of this research paper is to understand the role of poverty in youth engagement/employment pattern in India. The specific objectives are

To examine the pattern of youth development (employment, appropriate education, skill development and awareness about health) differentials linked with poverty in India.
To know the extent of youth economic engagement in the development of India and its States.

Data and methodology

The data for this paper is derived from Youth in India Situation and Needs Study, which was conducted by the International Institute for Population Sciences (IIPS), Mumbai and Population Council, New Delhi, in 2006–2007. It covers six states, Rajasthan, Bihar, Jharkhand, Maharashtra, Andhra Pradesh (erstwhile) and Tamil Nadu reflecting the diversity and geographic coverage of India. This study covers 174,037 households and 50,848 young people (15–24 age group). The main domain of this data set covers a wide range of issues on young people’s livelihood, education, family life education, sex and sexuality, adolescence education dynamics . This study is best suited for this research as all of these young people were adolescents 6 years ago and recent behaviour and economic participation issues can be explored.

Information on youth development in socioeconomic and demographic areas in India is not sufficient and systematic. However, this study is unique in gathering information on youth development (employment, appropriate education, skill development and awareness about health) and exploring its sociodemographic determinants in these six States. This research paper adopted some statistical techniques such as bivariate and multivariate analysis, and logistic regression. Apart from this secondary data set, I have linked youth related issues with data from Census 2011. The term used in this paper as employment (currently those who are working), un-employment(those who are actively searching employment are not getting at existing wage rate) and labor force (currently working and same time unemployed).

Findings and discussions

In Table 1 , the percentage of various age groups to the total age group has been estimated from Census 2011. The adolescent age group (10–19 years) and youth age group (15–24 years) form a significant section of the total population of India. India can realize the demographic dividend by enabling and empowering more youth through targeted areas such as skill development, appropriate education, healthy lifestyle and non targeted areas such as food subsidies and employment opportunities.

Table 1

Percentage of various age groups in India, 2011

Source: Estimated from Census age wise final data, 2011

In Table 2 , the work participation rate among youth is explained by analyzing the data of Census 2011. There is a significant differential in work participation, among various youth categories—the age group, 15–19 years, indicates 25.5 per cent compared to 49.8 per cent in the age group, 20–24 years. In the age group 15–24 years, the work participation is 36.9 per cent, compared to 39.8 per cent among all ages. Gender differentials in work participation are significant, that is, for male youth, it is 47.5 per cent, while for female youth, it is only 25.4 per cent. This indicates that women work participation has to increase considerably for their development. A country will realize its demographic dividend when both male and female youth development in terms of higher education, work participation, skill development and healthy lifestyle is achieved equally. Rural youth have better (41.6 %) work participation compared to their urban counterparts (27.1 %). This may be because urban youth (15–24 years) concentrate more on higher education and have an urban lifestyle.

Table 2

Total work participation rate among youth in India 2011

Source: RGI and UNFPA, adolescents and youth profile in India, 2011 (based on Census 2011)

Work participation rate trend and differentials among youth in India from 1981 to 2011 Census is discussed in Table 3 , which shows that the work participation rate among youth (15–24 years) has decreased for total, male female, rural and urban respectively. In 1981, total youth work participation rate was 47.1 per cent, which reduced to 36.9 per cent in 2011 and this trend was found in all categories. Rural youth work participation seems to be reducing more when compared to the others. Current educational opportunities offered to youth seem to lead towards youth development on the whole.

Table 3

Work participation rate trend and differentials among youth in India (1981–2011)

Source: RGI and UNFPA, adolescents and youth profile in India, 2011 (based on Census, 2011)

Figure 1 shows the work participation rate among the youth in the States/Union Territories (UTs) of India. The figure indicates that the work participation among youth in small UTs like Daman and Diu is the highest (61.8 %) followed by Dadra Nagar Haveli (56.3 %) and the lowest (15.6 percent) is in Lakshadweep followed by Kerala (20.6 %). The national average of youth work participation is 36.9 per cent. States/UTs with high youth work participation, above the national average, are (erstwhile) Andhra Pradesh, Assam, Maharashtra, Jharkhand, Meghalaya, Odisha, Mizoram, Karnataka, Gujarat, Madhya Pradesh, Himachal Pradesh, Sikkim, Nagaland, Rajasthan, Chhattisgarh and below national average are Puducherry, Andaman and Nicobar Islands, Jammu and Kashmir, Haryana, Chandigarh, Uttar Pradesh, Punjab, Uttarakhand, Tripura, Bihar, Tamil Nadu, Arunachal, West Bengal, Goa and Manipur.

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Work participation rate among youth in states/UTs of India, 2011. Source: Registrar General of India (RGI )and UNFPA, Adolescents and youth profile in India, 2011 ( Based on Census,2011) (include ‘erstwhile’ before Andhra Pradesh)

In Table 4 , the percentage of youth employment by wealth index in six states has been presented. The finding clearly indicates that fewer youth (13 %) from the poorest of the poor (quintile-1) households are employed compared to youth from the richest (quintile-5) households (22.3 %) in total for the six states under study. This finding shows that more youth in the age group (15–24 years) from the poorer strata of society are unemployed. This need for unemployment, perhaps, is a reflection of their poor economic condition, lack of monetary resources to fund education or familial insistence. Poverty has a great impact on youth development in every quintile, in all the six states. There are some differentials in negative youth development, which affect youth development due their employment at an early age and lack of proper education. These factors make them feel insecure.

Table 4

Percentage of youth employment by wealth index in six states

Table 5 presents the percentage of youth are not in labour force by wealth index in the six States under study. The findings indicate that there are fewer youth from the poorest of the poor (quintile-1) households (56.2 %) are not in the labour force compared to youth from the richest (quintile-5) households (71.9 %) in the six states. All the six states in this study show the same trend. This finding shows that more youth in the age group, 15–24 years from the poorer strata of society are not in the labour force. In other words, it indicates that due to familial constraints and their poor economic condition, they are not in the labour force. Poverty has a negative impact on youth development in every quintile in all the six states.

Table 5

Percentage of youth are not in labour force by wealth index in six states

Table 6 shows the percentage of youth currently not working by wealth index in these six States. The finding clearly indicates that fewer youth (36.4 %) from the poorest of the poor households (quintile-1) are currently not working compared to youth (70.4 %) from the richest households (quintile-5) in these six States. This trend among the richest and the poorest youth is the same for all these six these States. This finding shows that more youth in the age group, 15–24 years from the poorer strata of society are currently working. This reflects that poverty and economic restraints have prevented these youth from acquiring further education, which affects their development. In other words, it indicates, they are not in higher education or due to their bad economic condition, they are force to work currently in any form for them and their family. Poverty has an great impact in youth development found in this all six states as in every quintiles, there is some differentials in youth development in negative condition. Within states also similar trend. This will affect the youth development due their current working condition in this earlier age and not getting the appropriate education and healthy condition for their healthy lifestyle.

Table 6

Percentage of youth currently not working by wealth index in six states

The percentage of youth who are employment, in the labour force and currently not working by gender and wealth index has been explained in the above Table 7 . The findings show that fewer youth from the poorest households are employed (13 %), are in the labour force (56.1 %) and currently not working (36.4 %) compared to youth from the richest households (22.3 %), who are in the labour force (71.9 %) and currently not working (70.4 %) in total for both genders. The trend is similar for both male and female youth. In all these three economic parameters, females are at a disadvantage—total employment for male youth is 16 per cent compared to 14.1 per cent for female youth; 71.1 percent of male youth are in the labour force compared to 39.7 per cent for female youth, and 59.9 per cent of male youth are currently not working compared to 32.2 per cent of female youth. Female youth are less in employment, in labour force and currently working compared to male youth in all five ladders or economic conditions (Q-1, Q-2,Q-3, Q-4 and Q-5) respectively. It clearly shows that poor female youth in India are in a worse situation due to their deprivation. Poverty and other social factors contribute to their lagging behind. This female youth mass is a big segment of the Indian population. It is only when they are given appropriate education and equipped with skills and a healthy lifestyle that Indian youth can reap the demographic dividend of our country. These issues have been emphasized by the recent National Youth policy ( 2014 ) framework by the Government of India, Ministry of Youth Affairs and Sports.

Table 7

Percentage of Youth employment, in labour force and currently not working by gender and wealth index

The percentage of youth employed, in the labour force and currently not working by rural, urban with wealth index has been explained in the above Table 8 . Findings show that fewer youth from the poorest households are employed (13 %), in the labour force (36.4 %) and currently not working (36.4 %) compared to youth from the richest households, who are higher in employment (22.3 %), in the labour force (70.4 %) and currently not working (70.4 %) in total for both rural and urban areas respectively. There are similar trends for both rural and urban youth in these six states. In all these three economic parameters rural youth are at a disadvantage of 14.4 per cent of rural male youth are employed compared to 16.9 per cent of urban youth, 44.5 per cent of rural youth are in the labour force compared to 66.8 per cent of urban youth and 44.5 per cent of rural youth are currently not working compared to 66.8 per cent of urban youth. Rural poor youth are less in employment, in labour force and currently not working compared to urban youth in all five ladders or economic conditions (Q-1, Q-2,Q-3, Q-4 and Q-5) respectively. Rural youth comprise 18.9 per cent of the population, while urban youth comprise 19.7 per cent of the population according to Census 2011. It is therefore necessary to focus on equipping rural youth with appropriate education and skills so as to foster youth development in India.

Table 8

Percentage of youth employment, in labour force and currently not working by rural and urban with Wealth Index

In the above Table 9 , the percentage of youth employed by their education level has been explained. Findings show the levels of employment for youth with less than 5 years of schooling in Bihar (14.9 %) compared to those from the erstwhile State of Andhra Pradesh (.8 %). It clearly shows that at the same education level, youth are at a greater disadvantage in Andhra Pradesh compared to those in Bihar. Andhra Pradesh youth should promote more youth development programmes, especially for youth with lower levels of education. Among youth with higher levels of educational (13 years of schooling and above) Jharkhand youth have a higher employment percentage (42.5 %) compared to those from erstwhile Andhra Pradesh (9.8 %). Findings also show that youth in Rajasthan have higher levels of education than those in other all the other states and that youth from Jharkhand are the best among all these six states for total categories.

Table 9

Percentage of youth employment by their educational level in six states

In the above Table 10 , the percentage of youth currently not working by their educational level has been explained. There are no big differentials in youth currently not working. One important finding is that the number of less educated youth currently working from all these six states is higher compared to highly educated youth. Youth who are not educated and are compelled to work in unhealthy surroundings, are deprived of higher education and a healthy lifestyle. Education determines positive youth development in these six States.

Table 10

Percentage of youth currently not working by their education and wealth index in six states

In Table 11 , the percentage of youth employed by their father’s education and poverty have been explained. Analysis shows that the father’s educational level has an impact on youth development in general. Youth from illiterate father are less (8.8 %) employed compared to youth those fathers with 12 years of education and above (35.9 %) under total and it is same trend for all poverty level. This indicates that the higher the father’s level of education, the greater the employment for the son/daughter. The five categories of wealth quintiles also indicate the same pattern. So, the father’s educational level is also an important factor of youth development in India.

Table 11

Percentage of youth employment by father’s education and poverty status in india

In Table 12 , the percentage of youth employment by their father’s education and poverty in six states has been presented. Analysis shows that the father’s educational level has an impact on youth development in general. Youth from illiterate father are less (8.8 %) employed compared to youth those fathers with twelve years of education and above (35.9 %) under total and it is same trend for all poverty level. It clearly shows that more sons/daughters of illiterate fathers are employed compared to those whose fathers with higher levels of education. Five categories of quintiles and all six states also indicate the same pattern. Thus, the father’s educational level is an important factor of youth development in these six states.

Table 12

Percentage of youth employment by father’s education and wealth index in six states

To understand the determinants of youth unemployment, a logistic regression has been carried out as shown in Table 13 . The dependant variable is dichotomous, that is ‘1’ for youth unemployment and ‘0’ for youth employment. The independent variables are sex, age of youth, caste of respondent, religion, education of youth, education of father, standard of living and States. It is found that standard of living, education of father, type of school and education of youth are significant predictors of youth unemployment in these six states. For example, the odd of 12 years and above schooling of youth is 6.40 times higher employment rate compared to those youth have only studied 5–9 years of schooling. This indicates that more the years of schooling among the youth, less the unemployment rate in them.

Table 13

Logistic regression of unemployment among youth (1 = unemployment and 0 = employment)

The findings suggest that wealth index or standard of living (SLI) directly influences and determines youth development in India. Youth from the poorest households (quintile-1) are in the labour force and are more deprived or unemployed compared to youth from the richest households (quintile-5) and also those from the other three quintiles/economic levels of households in these six states. The father’s education and education of youth is the second pillar of youth development in India, which is influenced by the educational level of both. The higher the education of the father, the lesser the number of youth working in the labour force. These six States have differ in the patterns of youth development. Moreover, rural youth are more disadvantaged than urban youth, and female youth are more disadvantaged than male youth in these six states of India, irrespective of caste and region. Poverty/wealth index is an influential factor for youth development in India, which may be considered the first pillar of youth development. In every situation, the wealth index clearly shows that the lower the economic condition of the household, the more disadvantaged the youth. Poverty definitely leaves its mark on youth development in India.

Limitations

“This paper makes an attempt to reflect about the youth development pattern in India by using the data from Youth in India: Situation and Needs (2006–2007) although it’s sample size is small for generalizing the facts for whole India”. However, this data set is pioneer in the context of youth related information in Indian context.

Acknowledgements

I want to acknowledge to Prof. Sanjay Kumar Mohanty, Visiting Scientist, Harvard Center for Population and Development Studies (HCPD), Harvard School of Public Health, Harvard University, USA for giving good suggestions and feedback to this paper.

Paper presented in International Conference Special Meeting: Positive Youth Development (PYD) in the Context of the Global Recession organized by Society for Research in Child Development from 23 to 25 October 2014 Prague, Czech Republic.

Competing interests

There is no any competing interest of both financial and non-financial connection to this paper development and preparation. It is solely responsible by submitting author stated that there is no any competing interest.

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Data on what Indians earn does have plenty to reveal of poverty in India

On average, a casual wage worker is earning less than both the minimum wages and Rangarajan poverty line in 2022-23.

While a poverty line needs to be determined for use with fresh data on consumption spending, we have income readings that offer some clarity on the level of deprivation within the country.

Even though the fact-sheet on the Consumption Expenditure Survey (CES) has been officially released, the debate on poverty is far from over. Given that the new CES is based on a completely new survey design, the only way to resolve this issue is to have an expert committee decide on the appropriate poverty line to be used with these CES readings. Until that happens, the debate on poverty is likely to continue.

But that does not mean that we can’t get an idea of the level of poverty. The best alternative is to examine the level of wages or earnings of the poorest group of wage workers. This is not a new idea. In fact, the initial poverty lines were anchored to the minimum wages of casual unskilled manual labourers, since they inhabit the poorest category of households. Further, the methodology of setting minimum wages is linked to a minimum requirement of food and some forms of non-food expenditure.

Minimum wages for unskilled workers in areas with lowest urbanization or rural areas for 2023 was ₹ 424 per day, as per a government notification. For 2024, it is ₹ 449 per day. This is lower than the price-adjusted minimum wages of ₹ 483 in 2022-23, as per the suggestion of the labour ministry expert committee. The updated Rangarajan poverty line for 2022-23 at ₹ 1,837/ ₹ 2,603 per month per person for rural/urban areas, respectively, implies a family poverty line of ₹ 9,185/ ₹ 13,015, assuming a five-member family. Based on the actual number of days worked in a month from the Periodic Labour Force Survey (PLFS), a wage worker with a family to support would need minimum earnings of ₹ 390/552 per-day in rural/urban areas to cross the poverty line. For all of India, it would imply a poverty line of ₹ 445 per day, slightly higher than the government notified minimum wages.

What is the actual level of wages received by casual wage workers? According to labour bureau data, the average wage in agricultural occupations in January 2023 was ₹ 362 per day. It was higher in non-farm occupations, at ₹ 412, still lower than minimum wages. Another data source are wages and earnings reported by the PLFS, for which the 2022-23 report is available. According to PLFS readings, casual workers in rural areas received wages of ₹ 383 in the January-March 2023 quarter. This was only ₹ 310 per day in case of agricultural workers, lower than the estimate reported by the labour bureau and almost two-thirds of the specified minimum wages.

On average, a casual wage worker is earning less than both the minimum wages and Rangarajan poverty line in 2022-23. We also have estimates from the India Employment Report (IER) 2024. As per the report, brought out by the International Labour Organization and Institute for Human Development, 52% of all casual workers did not receive the minimum wages. 76% of workers in agriculture and 70% in construction got wages lower than minimum wages. It is not just casual wage workers who received wages less than the notified minimum, but also regular workers. The proportion of regular workers whose daily earnings were less than minimum wages was 41%. Together, regular and casual wage workers account for almost half of all workers in 2022-23. And almost 45% of them were earning less than minimum wages. The proportion of workers who earned less than the monthly sum needed to cross the Rangarajan poverty line was a fifth.

The IER also confirms the trend of a steady decline since 2011-12 in real wages of regular workers. While casual wage worker wages based on PLFS increased between 2011-12 and 2022-23, the wage growth rate was half the pace observed between 2004-05 and 2011-12. However, for casual wages, labour bureau data suggests a decline in real non-farm wages, with agricultural wages increasing at less than 1% per year in the last decade.

While these are not precise estimates, the wage and earnings data we have is comprehensive enough to suggest a significant proportion of Indians still live in poverty. A similar calculation for 2011-12 suggests that while poverty may have declined since then, it is only slightly lower.

The issue is not just of estimation of poverty, but a larger one of declining employment quality in India and meagre earnings for the majority of workers, including better-paid regular workers. The claim of India having eliminated extreme poverty may work as political rhetoric, but it may be at the cost of ignoring the stark reality of poorly paid workers and worsening employment quality.

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3. problems students are facing at public k-12 schools.

We asked teachers about how students are doing at their school. Overall, many teachers hold negative views about students’ academic performance and behavior.

48% say the academic performance of most students at their school is fair or poor; a third say it’s good and only 17% say it’s excellent or very good.
49% say students’ behavior at their school is fair or poor; 35% say it’s good and 13% rate it as excellent or very good.

Teachers in elementary, middle and high schools give similar answers when asked about students’ academic performance. But when it comes to students’ behavior, elementary and middle school teachers are more likely than high school teachers to say it’s fair or poor (51% and 54%, respectively, vs. 43%).

A horizontal stacked bar chart showing that many teachers hold negative views about students’ academic performance and behavior.

Teachers from high-poverty schools are more likely than those in medium- and low-poverty schools to say the academic performance and behavior of most students at their school are fair or poor.

The differences between high- and low-poverty schools are particularly striking. Most teachers from high-poverty schools say the academic performance (73%) and behavior (64%) of most students at their school are fair or poor. Much smaller shares of teachers from low-poverty schools say the same (27% for academic performance and 37% for behavior).

In turn, teachers from low-poverty schools are far more likely than those from high-poverty schools to say the academic performance and behavior of most students at their school are excellent or very good.

Lasting impact of the COVID-19 pandemic

A horizontal stacked bar chart showing that most teachers say the pandemic has had a lasting negative impact on students’ behavior, academic performance and emotional well-being.

Among those who have been teaching for at least a year, about eight-in-ten teachers say the lasting impact of the pandemic on students’ behavior, academic performance and emotional well-being has been very or somewhat negative. This includes about a third or more saying that the lasting impact has been very negative in each area.

Shares ranging from 11% to 15% of teachers say the pandemic has had no lasting impact on these aspects of students’ lives, or that the impact has been neither positive nor negative. Only about 5% say that the pandemic has had a positive lasting impact on these things.

A smaller majority of teachers (55%) say the pandemic has had a negative impact on the way parents interact with teachers, with 18% saying its lasting impact has been very negative.

These results are mostly consistent across teachers of different grade levels and school poverty levels.

Major problems at school

When we asked teachers about a range of problems that may affect students who attend their school, the following issues top the list:

Poverty (53% say this is a major problem at their school)
Chronic absenteeism – that is, students missing a substantial number of school days (49%)
Anxiety and depression (48%)

One-in-five say bullying is a major problem among students at their school. Smaller shares of teachers point to drug use (14%), school fights (12%), alcohol use (4%) and gangs (3%).

Differences by school level

A bar chart showing that high school teachers more likely to say chronic absenteeism, anxiety and depression are major problems.

Similar shares of teachers across grade levels say poverty is a major problem at their school, but other problems are more common in middle or high schools:

61% of high school teachers say chronic absenteeism is a major problem at their school, compared with 43% of elementary school teachers and 46% of middle school teachers.
69% of high school teachers and 57% of middle school teachers say anxiety and depression are a major problem, compared with 29% of elementary school teachers.
34% of middle school teachers say bullying is a major problem, compared with 13% of elementary school teachers and 21% of high school teachers.

Not surprisingly, drug use, school fights, alcohol use and gangs are more likely to be viewed as major problems by secondary school teachers than by those teaching in elementary schools.

Differences by poverty level

A dot plot showing that majorities of teachers in medium- and high-poverty schools say chronic absenteeism is a major problem.

Teachers’ views on problems students face at their school also vary by school poverty level.

Majorities of teachers in high- and medium-poverty schools say chronic absenteeism is a major problem where they teach (66% and 58%, respectively). A much smaller share of teachers in low-poverty schools say this (34%).

Bullying, school fights and gangs are viewed as major problems by larger shares of teachers in high-poverty schools than in medium- and low-poverty schools.

When it comes to anxiety and depression, a slightly larger share of teachers in low-poverty schools (51%) than in high-poverty schools (44%) say these are a major problem among students where they teach.

Discipline practices

About two-thirds of teachers (66%) say that the current discipline practices at their school are very or somewhat mild – including 27% who say they’re very mild. Only 2% say the discipline practices at their school are very or somewhat harsh, while 31% say they are neither harsh nor mild.

We also asked teachers about the amount of influence different groups have when it comes to determining discipline practices at their school.

67% say teachers themselves don’t have enough influence. Very few (2%) say teachers have too much influence, and 29% say their influence is about right.

A diverging bar chart showing that two-thirds of teachers say they don’t have enough influence over discipline practices at their school.

31% of teachers say school administrators don’t have enough influence, 22% say they have too much, and 45% say their influence is about right.
On balance, teachers are more likely to say parents, their state government and the local school board have too much influence rather than not enough influence in determining discipline practices at their school. Still, substantial shares say these groups have about the right amount of influence.

Teachers from low- and medium-poverty schools (46% each) are more likely than those in high-poverty schools (36%) to say parents have too much influence over discipline practices.

In turn, teachers from high-poverty schools (34%) are more likely than those from low- and medium-poverty schools (17% and 18%, respectively) to say that parents don’t have enough influence.

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Table of contents, ‘back to school’ means anytime from late july to after labor day, depending on where in the u.s. you live, among many u.s. children, reading for fun has become less common, federal data shows, most european students learn english in school, for u.s. teens today, summer means more schooling and less leisure time than in the past, about one-in-six u.s. teachers work second jobs – and not just in the summer, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

Global Lessons for improving Early Childhood Education in Latin America and the Caribbean

Early childhood education is not just a school issue. Investing today in the education of the youngest members of the household can ensure the human capital needed for more equitable societies. We talked about this with Norbert Schady, Chief Economist for Human Development at the World Bank , who brings lessons from other regions.

Why is it important to invest in early childhood education?

The early years of a child's life are when the basic architecture of the brain is literally formed. And the absence of important investments at that time, of important nurturing, attachment or nurturing stimuli, has negative consequences for the rest of life.

So, investing in early childhood really lays the foundation, the foundation for all the investments that occur later. Following children from two, three years of age to forty years of age, it is clear that children who have low levels of development in early childhood suffer in different dimensions.

In adulthood they have lower incomes, lower job probability, higher crime rates, fewer years of schooling completed, and so on. So it really is a critical investment that we can make in the early years.

What lessons could we bring from other countries for the Latin American and Caribbean region?

I would like to highlight two in particular. The first is that families are absolutely critical and, consequently, it is very important to look at the parenting practices that parents have in their homes.

In many countries there has been a lot of expansion of coverage of different services, kindergartens, preschools, and less attention has been paid to the quality of these services, but quality is absolutely fundamental. Expanding without quality makes no sense, it may even be harmful to children, that is the second lesson.

What is the future of early childhood education?

Let's say in the short term future and in the long term future. In the short-term future I think we have to see how we can recover what was lost during the pandemic because it is still there. In the more immediate term, we have to recover the losses from the pandemic and in the slightly more medium term, although we can't wait, but in the more medium term is how do we make sure that the services that we provide are truly those that benefit children.

The State of Ceara and the City of Sobral, in Brazil, are Role Models for Reducing Learning Poverty

Interview with Norbert Schady: Global Lessons for improving Early Childhood Education in Latin America and the Caribbean

Interview with Emanuela Di Gropello: The importance of investing in a high-quality Early Childhood Education in Latin America and the Caribbean

Interview with Mauricio Pineda y Alejandra Posada: Early childhood education, an opportunity to strengthen El Salvador's human capital

Interview with Claudia Lagos: "Children are not a future hypothesis"

Interview with Juan Maragall (IDB): Improving early childhood education through interactions

Interview with Francisco Lima: Keys to literacy success for Sobral's children

Download the publication 'Quality Early Learning: Nurturing Children’s Potential'

IMAGES

(PDF) Extent of Poverty in India: A Different Dimension
How India has reduced poverty in 10 years between 2005 and 2015
India halves poverty in 10 years, says latest UN report
Literature Review on Poverty in India
Poverty In India Essay
🆕Group Discussion on Poverty in India👉 Group Discussion Video I Talent Battle GD Series

VIDEO

India's Poverty was well planned
135Million Indians came out of poverty trap in five years
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|| ग़रीबी सबको रुलाती है 😭😢|indiapoverty report #poverty
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Main Causes of Poverty in India

COMMENTS

PDF A Comprehensive Analysis of Poverty in India
This paper offers a comprehensive analysis of poverty in India. It shows that no matter which of the two official . poverty lines is used, poverty has declined steadily in all states and for all social and religious groups. Accelerated growth between fiscal years 2004-2005 and 2009-2010 led to an accelerated decline in poverty rates. Moreover,
Multidimensional poverty and growth: Evidence from India 1998-2021
1. Introduction. The growth-poverty nexus has been a central focus of research and academic discourse for decades. While the positive impact of economic growth on poverty reduction has long been emphasized, 1 the reverse relationship from poverty to growth has only received modest attention. This question assumes particular significance in the post-pandemic era, as the global COVID-19 ...
Escaping and Falling into Poverty in India Today
A growing literature on the dynamics of poverty has focused more on the questions of chronic poverty and poverty traps than on the questions of entries and exits that we have emphasized (Shepherd and Mehta 2006; Glauben et al., 2012; Naschold 2012). While analyses of poverty durations are an obvious advance over earlier research that could look ...
PDF MULTIDIMENSIONAL POVERTY IN INDIA SINCE 2005-06
Poverty in rural India fell from 32.59% to 19.28% while in urban areas it declined from 8.65% to 5.27%. Thus, rural population witnessed a larger decline in poverty as compared to urban population. 1. Significant reductions (improvement) were observed in all 12 indicators over the two time periods:
Four questions and answers on growth and poverty reduction in India
PDF | On Dec 1, 2016, Gaurav Datt and others published Four questions and answers on growth and poverty reduction in India | Find, read and cite all the research you need on ResearchGate
Poverty in India in the face of Covid‐19: Diagnosis and prospects
The onset of the Covid‐19 pandemic in early 2020 has dampened these ambitions. Nowhere is this more evident than in India, a country where poverty reduction during the first decades of the 2000s had been remarkable, but where the impact of the Covid pandemic has been staggering in terms of both public health and economic livelihoods.
Pandemic, Poverty, and Inequality: Evidence from India
The paper presents estimates of poverty [extreme poverty PPP .9 and PPP$3.2] and consumption inequality in India for each of the years 2004-5 through the pandemic year 2020-21. These estimates include, for the first time, the effect of in-kind food subsides on poverty and inequality. Extreme poverty was as low as 0.8 percent in the pre-pandemic year 2019, and food transfers were instrumental ...
Multidimensional poverty in India: patterns of reduction across
Data. For the estimation and analysis of multidimensional poverty and deprivations in India in relation to SDGs across castes/ethnicity, religion and geographic region, we have used the unit level data from the National Family Health Survey (NFHS) of the latest three rounds NFHS 3 (2005-06), NFHS 4 (2015-16) and NFHS 5 (2019-21) which is conducted by the International Institute of ...
PDF A Comprehensive Analysis of Poverty in India
The original ofﬁcial poverty estimates in India, provided by the Planning Commission, were based on the Lakdawala poverty lines, so named after Professor D. T. Lakdawala who headed a 1993 expert group that recommended these lines. ∗Arvind Panagariya is Professor at Columbia University and Megha Mukim is an Economist at the World Bank. The
The Impact of COVID-19 on Poverty Estimates in India: A Study Across
The World Bank's latest forecast (Lakner et al., 2021) for the economic pushback of the pandemic in the year 2020 stands at 119-124 million of the global population falling into extreme poverty (those living under $1.90 per day), of which around 60% belong to South Asia.The International Labour Organization estimated around 140 million of global employment loss in the year 2020.
Income and Poverty in India: Social Inequality Across States
Multi-dimensional poverty reduction in India, 2005/6-2015/16: Still a long way to go but the poorest are catching up, Oxford Poverty & Human Development Initiative (OPHI), OPHI Research in Progress 54a, Oxford Department of International Development, University of Oxford. Government of India. (2015a). Socio-economic and caste census, 2011.
The Great Indian Poverty Debate, 2.0
A new World Bank paper using private-sector survey data finds the share of people living below $1.90 per day has been falling, but is higher than we thought, at about 10 percent. A rival paper from India's representative at the IMF says India has joined China in (almost) fully eradicating extreme poverty. Both estimates seem optimistic given ...
India
Poverty in India, like its population, is predominantly rural but remarkably responsive to economic growth. As the economy grows, poverty diminishes, faster when growth . ... Global data and statistics, research and publications, and topics in poverty and development. WORK WITH US. Jobs, procurement, training, and events.
Poverty in India: Measurement, Trends and Other Issues
Poverty in India can be defined as a situation when a certain section of people are unable to fulfill their basic needs. India has the world's largest number of poor people living in a single country.
PDF Multidimensional poverty in India: a study on regional disparities
Abstract The primary objective of this study is to investigate the regional disparities of multidimen-sional poverty (MPI) in the context of India. This study to our knowledge is the first of its kind which examined MPI disparity at a regional level. The study has classified the geographic area of India into six regions: Northern, Eastern ...
Introduction: Analysing Poverty in India
Poverty in India has proven to be inflexible ever since the country gained its independence more than fifty years ago, prompting the question of what the role of the state or public policy is in reducing poverty in India. ... The chapter ends with a discussion of the research questions, theoretical implications, and original contribution of the ...
Poverty and Inequality in India: An Exploratory Analysis
Abstract. India is a country characterized by multi-layered diversity and cultural heterogeneity where different types of inequalities and poverty have always been a fact of life. Since independence in 1947, she followed a development policy based on interventionist central planning and import substitution with the objective of reducing ...
Measuring Trends in Multidimensional Poverty
This article questions the methodology adopted in NITI Aayog's discussion paper on the progress of multidimensional poverty in India between 2005-06 and 2022-23. It highlights some of the limitations of the concept of multidimensional poverty and cautions against measuring the multidimensional poverty index through interpolation and extrapolation of past trends. It shows that the rate of ...
Poverty and inequality in India
Premium Statistic Distribution of households below poverty line in India 2019-2020, by quantile Premium Statistic COVID-19 impact on rural and urban employment India 2020, by type
Youth development in India: does poverty matter?
Poverty/wealth index is an influential factor for youth development in India, which may be considered the first pillar of youth development. In every situation, the wealth index clearly shows that the lower the economic condition of the household, the more disadvantaged the youth. Poverty definitely leaves its mark on youth development in India.
(PDF) A Study on Poverty and Hunger in India
Poverty in India is widespread, with the nation estimated to have a third of the. world's poor. In 2010, the World Bank reported that 32.7% of the total Indian people falls below. the ...
The 'wall': reflections on youth aspiration, education and social
3. This research on young people in India, social change, and politics, was initiated by the Institute of South Asian Studies at the National University of Singapore and conducted in partnership with colleagues in Delhi, at the Centre for the Study of Social Systems of Jawaharlal Nehru University, in Bihar (the Asia Development Research Institute), and in Tamil Nadu (the Madras Institute of ...
Data on what Indians earn does have plenty to reveal of poverty in India
The updated Rangarajan poverty line for 2022-23 at ₹ 1,837/ ₹ 2,603 per month per person for rural/urban areas, respectively, implies a family poverty line of ₹ 9,185/ ₹ 13,015, assuming a ...
Global India Frontiers Conference
Details. Global India Frontiers seeks to bring together multiple themes related to India's future that are often discussed separately in disciplinary silos. It features frontier research topics across key themes of economy and politics, inclusion, sustainability, innovation, arts, and U.S.-India partnerships. The goal is to feature ...
(PDF) Poverty in India -A Study of Rural Poverty
PDF | On Dec 31, 2020, Dr Sharath A.M published Poverty in India -A Study of Rural Poverty | Find, read and cite all the research you need on ResearchGate
Problems students are facing at public K-12 schools
Major problems at school. When we asked teachers about a range of problems that may affect students who attend their school, the following issues top the list: Poverty (53% say this is a major problem at their school) Chronic absenteeism - that is, students missing a substantial number of school days (49%) Anxiety and depression (48%) One-in ...
Global Lessons for improving Early Childhood Education in Latin America
With 189 member countries, staff from more than 170 countries, and offices in over 130 locations, the World Bank Group is a unique global partnership: five institutions working for sustainable solutions that reduce poverty and build shared prosperity in developing countries.