Fact-checked by Grok 2 weeks ago

Below Poverty Line

The below poverty line (BPL) threshold designates the minimum income or consumption level required to meet essential human needs, with individuals or households falling beneath it classified as living in for the purposes of statistical tracking and eligibility. Globally, the applies an international line of $2.15 per person per day (in 2017 ), below which approximately 648 million people—around 8% of the world's —subsisted as of recent estimates, primarily in and . National variants, such as the U.S. Federal Poverty Level set by the Department of Health and , calibrate thresholds by size (e.g., $14,891 annually for an in 2023) and update them yearly to gauge program qualifications, though these derive from outdated methodologies originally tied to food costs representing one-third of budgets. These measures facilitate and progress monitoring toward goals, yet they embody significant limitations rooted in arbitrary and incomplete capture of lived hardship. Critics highlight that BPL calculations often ignore non-food expenses like , healthcare, and transportation; regional price disparities; and multidimensional deprivations such as or access, potentially understating 's scope— for instance, half the global population lives below $6.85 daily when broader lines are applied. Empirical assessments reveal inconsistencies, including static benchmarks that fail to reflect inflation or behavioral adaptations, leading to misleading trends in official claims. In policy contexts, particularly in aid-dependent economies, BPL lists have been prone to errors of exclusion and inclusion, driven by subjective criteria or administrative capture, which undermine targeting efficiency and fiscal sustainability. Such flaws underscore the metric's role as a pragmatic but , better supplemented by causal analyses of productivity barriers and institutional incentives than relied upon in isolation.

Origins and Historical Context

Post-Independence Conceptualization

Following India's independence in 1947, the conceptualization of a poverty line emerged as part of broader efforts, initially focusing on minimum levels rather than targeted welfare identification. In 1962, the Planning Commission established a to quantify nationally, recommending a minimum per capita expenditure of Rs. 20 per month in rural areas at 1960-61 prices, derived from basic nutritional and non-food needs without explicit calorie benchmarks. This marked the first official post-independence attempt to define a separating those below adequate living standards, though it was not uniformly applied and emphasized aggregate incidence over household-level categorization. Subsequent refinements incorporated empirical data from National Sample Survey rounds, with economists V.M. Dandekar and N. Rath conducting the inaugural systematic poverty assessment in 1971 using 1960-61 NSS data. They proposed a poverty line based on expenditure sufficient to meet 2,250 calories daily in both rural and urban areas, estimating that approximately 40-50% of the population fell below this threshold, highlighting rural-urban disparities and the limitations of prior calorie-exclusionary approaches. This work shifted conceptualization toward nutritionally grounded expenditure norms, influencing later methodologies by prioritizing verifiable consumption data over normative minima. The framework solidified in 1979 through a Planning Commission chaired by Y.K. Alagh, which differentiated rural and urban poverty lines on nutritional criteria: 2,400 calories per day for rural residents and 2,100 for urban, augmented by non-food spending patterns observed in NSS data. This yielded base lines of Rs. 49.09 per capita monthly in rural areas and Rs. 56.64 in urban at 1973-74 prices, establishing a dual-normative standard that accounted for regional price variations and became the benchmark for official estimates into the 1990s. These efforts conceptualized poverty not merely as absolute deprivation but as a measurable gap in basic capabilities, laying groundwork for Below Poverty Line (BPL) lists used in welfare targeting, though early applications remained focused on macro-level planning rather than micro-identification.

Integration into Five-Year Plans

The concept of identifying households below the poverty line (BPL) was formally integrated into India's planning framework during the Eighth (1992–1997), when the first nationwide BPL was conducted in 1992 to support targeted for alleviation programs. This relied on self-reported to classify households, enabling the to prioritize subsidies and schemes like the Integrated Rural Development Programme (IRDP) for the poorest families, thereby shifting from broad-based to selective interventions aimed at reducing rates. The Ninth Five-Year Plan (1997–2002) built on this by conducting a second BPL census in 1997, which coincided with the launch of the Targeted Public Distribution System (TPDS) in June 1997. Under TPDS, BPL households received food grains at highly subsidized rates—such as 50 kg of or per family monthly at Rs 3 per kg—distinct from above-poverty-line (APL) categories, to enhance and nutritional outcomes for approximately 60 million identified BPL families initially. This integration facilitated better monitoring of program efficacy, with plan documents emphasizing through and asset creation for BPL beneficiaries. Further refinements occurred in the Tenth (2002–2007), which included a 2002 BPL census introducing deprivation-based scoring for rural households across 13 socio-economic indicators, such as housing quality, access to , and land ownership, with scores ranging from 0 to 4 to determine eligibility. This multi-dimensional approach supported the plan's target of reducing the ratio by 5 percentage points by 2007, informing allocations for schemes like the and Swarnajayanti Gram Swarozgar Yojana, which focused on BPL self-employment groups. Urban BPL criteria were similarly updated, emphasizing consumption expenditure below state-specific thresholds. The Eleventh (2007–2012) continued this trajectory with updated BPL parameters in 2007, incorporating additional factors like household size and vulnerability to align with goals, though implementation faced delays due to legal challenges over exclusion errors. BPL data thus became central to plan evaluations, enabling empirical tracking of trends—such as a projected decline from 27.5% in 2004–05 to under 15% by 2012—while highlighting issues like inclusion-exclusion inaccuracies estimated at 10–20% in surveys. Overall, BPL integration evolved from rudimentary income tests to robust targeting tools, underpinning fiscal transfers exceeding Rs 1 lakh crore annually by the later plans for welfare entitlements.

Methodologies and Criteria

Income-Based Poverty Thresholds

The income-based poverty thresholds in India, as applied to Below Poverty Line (BPL) classifications, primarily derive from per capita monthly consumption expenditure benchmarks established by expert committees under the erstwhile Planning Commission, serving as proxies for minimal income adequacy to meet basic nutritional and non-food needs. These thresholds originated with the Y.K. Alagh Working Group in 1979, which defined poverty lines based on a calorie norm of 2,400 kcal per capita daily in rural areas and 2,100 kcal in urban areas, translating to expenditure levels sufficient for those intakes plus minimal non-food outlays. This approach fixed rural poverty at approximately Rs. 49 per capita per month and urban at Rs. 57 in 1973-74 prices, emphasizing consumption over direct income measurement due to the volatility and underreporting of incomes in household surveys. Subsequent refinements, such as the D.T. Lakdawala Expert Group in 1993, extended these calorie-derived lines state-wise using uniform price indices, maintaining the focus on uniform all-India calorie standards while adjusting for regional cost variations; for 1993-94, this yielded rural thresholds around Rs. 205-281 monthly across states. The Committee in 2009 shifted methodology by adopting an urban mixed-consumption basket applied nationally, incorporating and expenditures, resulting in 2004-05 base year lines of Rs. 446.68 rural and Rs. 578.80 urban monthly, escalating to Rs. 816 rural and Rs. 1,000 urban by 2011-12 prices after adjustment. These figures equated to roughly Rs. 27 daily rural and Rs. 33 urban expenditure, capturing 29.8% of the population as poor in 2009-10, though critics noted the lines' , as they afforded only 1,880 rural and 1,720 urban calories daily, below normative requirements. The Committee in 2014 proposed higher thresholds—Rs. 972 rural and Rs. 1,407 urban monthly per capita in 2011-12 prices—incorporating a broader basket with 2,155 rural and 2,090 urban calories, plus fixed non-food norms like Rs. 600 urban , estimating 29.5% in 2011-12; this implied daily outlays of Rs. 32 rural and Rs. 47 urban. However, official estimates retained Tendulkar lines until the Commission's dissolution in 2015, after which ceased monetary computations, pivoting to multidimensional indices without updating expenditure thresholds. In BPL scheme implementation, states often adapt these national benchmarks into local caps or scoring systems, such as deeming households with annual incomes below Rs. 1-1.2 eligible in some regions, though empirical surveys prioritize verifiable data to mitigate self-reported biases. This consumption-centric approach reflects causal recognition that expenditures better indicate sustained welfare than fluctuating incomes, yet it has drawn scrutiny for undercounting amid rising non-food essentials like healthcare, where actual minimal viable incomes exceed threshold-implied levels by 20-50% in empirical studies.

Multi-Dimensional Scoring Systems

Multi-dimensional scoring systems for Below Poverty Line (BPL) identification in incorporate non-income indicators such as housing quality, asset ownership, type, and social vulnerabilities to assess deprivation levels, aiming to target benefits more effectively than income thresholds alone. These systems emerged as a response to the limitations of unidimensional measures, which often failed to capture chronic deprivations in , and living standards. The approach draws from empirical observations that manifests in overlapping deficits, with scoring mechanisms assigning points based on affirmative responses to deprivation criteria, followed by households against state-specific quotas. The 2002 Rural BPL Census introduced a pioneering score-based , evaluating over 100 million rural households across 13 socio-economic parameters, including food adequacy, clothing sufficiency, type of house, source of , , , and dependency on casual labor. Each parameter was scored on a 0-4 point scale for deprivations (e.g., kuccha house scored 4 points, partial scored variably), yielding a total score ranging from 0 (least deprived) to higher values indicating greater deprivation, though inverted rankings for exclusion. Households were categorized into automatic inclusion (e.g., scores reflecting extreme deprivation like landlessness and ), automatic exclusion (e.g., owning irrigated over 2.5 acres or mechanized assets), and a residual group ranked by score for state-determined cutoffs, typically excluding the top 10-20% to fit scheme coverage. This system covered approximately 36% of rural households as BPL, but faced challenges due to subjective scoring by enumerators. An urban variant used 10 parameters, similarly scoring for asset and habitation deficits. The Socio-Economic and Caste Census (SECC) 2011 refined this framework by integrating caste data and a hybrid scoring process for both rural and urban areas, covering 240 million rural and 100 million urban households. It employed seven automatic exclusion criteria (e.g., owning a motorized , government job, or house with three rooms), five automatic inclusion categories (e.g., destitutes, primitive tribal groups, manual scavengers), and, for the remaining households, a deprivation score derived from 14 rural or 16 urban parameters, such as landholding size, monthly income under Rs 5,000, SC/ST status, and female-headed households with no adult male member. Scores ranged from 0 to 52, with households ranked in ascending order (lower scores indicating higher deprivation) and cutoffs applied per state to allocate scheme beneficiaries, often targeting 20-40% coverage. This methodology emphasized verifiable via self-enumeration and , reducing enumerator , though data discrepancies arose from under-reporting assets. SECC data has since informed BPL lists for schemes like MGNREGA and PDS, with periodic updates. Complementing these targeting tools, the National Multidimensional Poverty Index (MPI), launched by in 2021 using the Alkire-Foster methodology, provides an analytical scoring system across 12 indicators in three dimensions— (nutrition, , ), (years of schooling, school attendance), and standard of living (cooking , sanitation, , , , assets, )—weighted at 1/3 each. A household is deemed multidimensionally poor if deprived in at least 33% of weighted indicators, with intensity measuring average deprivations; the MPI is the product of headcount and intensity. Drawing from data, the 2019-21 MPI identified 14.96% of the population (about 135 million people) as poor, down from 24.85% in 2015-16, informing policy but not direct BPL card issuance. This index prioritizes empirical robustness over administrative targeting, using household-level data validated through surveys rather than self-reported assets.

Socio-Economic and Caste Census Integration

The Socio-Economic and Caste Census (SECC) 2011 marked a departure from prior Below Poverty Line (BPL) surveys by integrating comprehensive socio-economic profiling with enumeration to rank households for targeting, rather than solely relying on proxies. Conducted across rural and under the Ministry of Rural Development, SECC employed a canvasser-based where enumerators collected data on 48 deprivation indicators for rural households and 31 for ones, enabling automatic exclusion of non-poor families (e.g., those with mechanized farming or government jobs) and inclusion of severely deprived ones (e.g., landless laborers with no able-bodied adults or dilapidated ). This process identified 10.69 rural households as deprived, facilitating evidence-based allocation of resources to schemes like the National Rural Employment Guarantee Act (MGNREGA). Integration of SECC data into BPL frameworks addressed exclusion errors in earlier income-centric censuses, such as the 2002 BPL survey, which had misclassified up to 60% of beneficiaries due to subjective scoring. By prioritizing objective deprivation cut-offs—such as households with illiterate members over 16 years or those relying on —SECC reduced reliance on local panchayat discretion, which often favored political allies over the needy. Empirical comparisons show that SECC's rural deprivation criteria aligned with 55-58% overlap in BPL identification when targeting similar proportions of households, though urban methodologies lagged in granularity, leading to persistent under-coverage in cities. Post-2011, SECC databases underpin beneficiary lists for over 30 central schemes, including Pradhan Mantri Awaas Yojana (PMAY) for housing and Deen Dayal Antyodaya Yojana for , with data exclusions applied to filter out 39.36% of rural households possessing indicators of relative affluence like ownership or residences. Despite enhancements in targeting efficiency—evidenced by a 14% reduction in leakages for MGNREGA job cards post-SECC linkage—critiques highlight data obsolescence, as no full recensus has occurred since 2011, potentially inflating errors amid economic shifts like post-2016 demonetization impacts on informal livelihoods. Rural SECC rankings also incorporate metrics to prioritize Scheduled Castes and Tribes in quota allocations, though verification through linkage has exposed duplicates, with 2.25 crore ghost beneficiaries purged by 2018.

Implementation and Coverage

Identification Processes and Cut-Offs

The identification of Below Poverty Line (BPL) households in for welfare entitlements, such as under the National Food Security Act (NFSA) 2013, is decentralized to states and union territories, which use the 2011 Socio-Economic and Caste (SECC) data as the foundational dataset for ranking and selection. SECC employs a multi-stage proxy-based process to circumvent direct income assessments, which are prone to underreporting and verification challenges, instead relying on observable socio-economic indicators collected via household surveys. This approach categorizes households through automatic exclusion of relatively better-off families, automatic inclusion of the most deprived, and scoring-based ranking of the remainder, enabling states to allocate benefits to priority households covering up to 75% of rural and 50% of urban populations nationwide. In rural areas, automatic exclusion applies to households meeting any of seven specified criteria signaling relative affluence, including possession of a motorized two-, three-, or four-wheeler (or mechanized agricultural equipment), a with a limit of ₹50,000 or more, a , 2.5 acres or more of irrigated land (or equivalent non-irrigated), any family member in a or permanent salaried job, payment by any member, or engagement in non-agricultural business by family members. Automatic inclusion targets five extreme deprivation categories: manual scavenger families, primitive tribal groups, persons with specified disabilities (e.g., mental or multiple), landless laborers residing in one room or kutcha houses, and destitute families dependent on beggary. The remaining households—comprising the majority—are assigned deprivation scores from 0 to 52 based on 46 indicators across housing, assets, , , and land ownership (e.g., 12 points for no adult member with education beyond secondary level, or lacking a dwelling). These scores facilitate ranking from highest deprivation (poorest) to lowest. Urban identification mirrors the rural framework but adapts to non-agricultural contexts, with automatic exclusion based on 16 criteria such as owning a three- or four-wheeler, air-conditioned vehicles, mechanized equipment, or PSU jobs, high-value assets like flush toilets with metered water, or professional occupations (e.g., doctors, lawyers). Automatic inclusion covers similar destitute groups, while the 48 deprivation indicators for ranking emphasize urban-specific vulnerabilities like residency, lack of durable housing, or manual labor in hazardous conditions. States verify SECC data through local gram panchayats or urban local bodies, often integrating linkage for de-duplication, though inclusion remains a continuous process allowing appeals and updates. Cut-offs are not nationally fixed but determined locally by states selecting the lowest-ranked (most deprived) households until NFSA coverage quotas are met, typically the bottom deciles or percentiles calibrated to demographic targets—e.g., excluding higher-scoring households to cap eligibility at state-specific estimates. This percentile-based thresholding, applied post-ranking, aims for but varies across states; for instance, some prioritize SECC scores alongside proofs below ₹10,000–₹20,000 monthly for ration card issuance, reflecting adjustments for and local costs unaddressed in the static 2011 data. As of 2025, SECC 2011 remains the baseline despite criticisms of , with states conducting periodic reverifications but no nationwide recensus implemented.

Beneficiary Entitlements and Schemes

Individuals identified as below the poverty line (BPL) in are entitled to subsidized access to essential commodities through the Public Distribution System (PDS), primarily under the Targeted Public Distribution System (TPDS) and the National Food Security Act (NFSA) of 2013. BPL households receive up to 35 kilograms of rice or wheat per month at highly subsidized rates, typically Rs. 2 per kg for wheat and Rs. 3 per kg for rice, compared to market prices exceeding Rs. 20-30 per kg as of 2024. The (AAY), a sub-scheme targeting the poorest among BPL families, provides 35 kg of foodgrains free of cost or at minimal charges to approximately 2.5 crore households as of 2023. Health entitlements for BPL beneficiaries include coverage under the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), launched in 2018, which offers up to Rs. 5 lakh per family annually for secondary and tertiary hospitalization, covering over 10 crore poor families identified via SECC 2011 data. This scheme has disbursed treatments worth over Rs. 1 lakh crore by 2024, focusing on surgical interventions and critical care otherwise unaffordable for BPL groups. Earlier programs like (RSBY), operational from 2008 to 2018, provided Rs. 30,000 annual coverage to BPL unorganized workers before merging into PM-JAY. Additional schemes linked to BPL status encompass financial assistance upon contingencies, such as the National Family Benefit Scheme (NFBS), which grants a one-time of Rs. 20,000 to BPL families upon the death of the primary breadwinner aged 18-60. Employment-linked entitlements include priority under National Rural Employment Guarantee Act (MGNREGA), guaranteeing 100 days of wage employment annually to rural BPL households, with wages indexed to at Rs. 200-300 per day across states in 2024. The Pradhan Mantri Garib Kalyan Anna Yojana (PMGKAY), extended through 2028-29, supplements PDS allocations with free additional foodgrains (5 kg per person monthly) for NFSA-covered beneficiaries, including BPL, reaching over 80 individuals amid post-2020 economic disruptions. BPL ration cards also facilitate access to state-specific subsidies, such as priority in housing under (PMAY) and scholarships via schemes like Post-Matric Scholarship for SC/ST/OBC students from BPL families, disbursing Rs. 10,000-50,000 annually depending on course level as of 2023. These entitlements are administered via biometric-linked PDS portals to reduce leakages, though coverage varies by implementation, with southern states like offering universal PDS expansions beyond strict BPL criteria.

Regional Variations and Case Studies

The identification and application of Below Poverty Line (BPL) status in demonstrate substantial regional variations, primarily driven by differences in state-level surveys, local cost-of-living adjustments, and administrative priorities under central guidelines. States establish distinct rural and poverty lines to reflect variations in prices and baskets, with rural thresholds typically lower than ones; for example, national per capita monthly expenditure cut-offs have been set around ₹1,284 in recent estimates, while rural lines incorporate scoring across 13 socio-economic indicators such as land ownership, housing quality, and access to sanitation. These adaptations stem from committees like the Tendulkar panel, which recommended state-specific lines to capture intra-country disparities, yet implementation often results in uneven coverage due to varying and exclusion caps imposed to limit beneficiaries to projected shares, sometimes capping BPL households at 10-20% in states with higher actual deprivation levels. In southern states like and , BPL processes benefit from stronger governance and higher baseline human development, leading to lower reported poverty headcounts—Kerala's multidimensional poverty index (MPI) fell to 0.55% by 2019-21, correlating with effective BPL targeting that minimizes exclusion errors through better enumeration and integration with schemes like the Public Distribution System (PDS). These regions exhibit reduced small-area variations in BPL card possession, with within-district standard deviations as low as 2.6% in some clusters, reflecting more uniform access influenced by high rates (over 94% in ) and remittance-driven rural economies that elevate household scores above cut-offs. Conversely, eastern and central states such as and face higher BPL proportions, with Bihar's MPI at 33.76% in 2019-21, where identification challenges include widespread under-enumeration due to remote terrains and , resulting in median within-cluster BPL card deviations up to 17.6% and persistent inclusion of non-poor households amid in surveys. A case study from illustrates successful regional adaptation: the state's 2011 BPL census, aligned with self-declaration methods, achieved near-universal coverage of eligible households for entitlements like subsidized under PDS, with exclusion rates below 5% as verified by audits, bolstered by decentralized panchayat-level verification that incorporates local and data to refine cut-offs beyond income alone. This contrasts with 's implementation, where the same 2011 census revealed over 40% rural households qualifying under loose criteria, yet leakages exceeded 50% in PDS deliveries due to ghost beneficiaries and poor , exacerbating regional disparities as migrant labor from Bihar often disqualifies sending households from stable BPL status upon return. Urban-rural divides amplify these patterns; in metropolitan clusters of , urban BPL thresholds capture informal workers effectively via consumption surveys, reducing MPI deprivations in sanitation by 20-30% post-2015, while rural Bihar lags with 28.81% MPI in Jharkhand-adjacent areas, where -based exclusions persist despite Socio-Economic Census integration.

Measured Reductions in Poverty Rates

Official estimates from India's National Sample Survey Office () consumption expenditure surveys indicate a decline in the poverty headcount ratio using the Tendulkar Committee's methodology, from 37.2% in 2004–05 to 21.9% in 2011–12. This reduction reflected improvements in per capita consumption, particularly in rural areas where the rate fell from 41.8% to 25.7%. However, the Rangarajan Committee's alternative methodology, which incorporated higher nutritional norms and included expenditures on and , estimated a higher rate of 29.5% for 2011–12, highlighting methodological sensitivities in poverty measurement. Post-2011–12, the absence of comparable NSSO large-sample surveys—often termed the "missing decade"—complicated direct income-based tracking, leading to reliance on alternative data sources and projections. analyses, drawing on household data and imputations, reported a further drop in (at $2.15 PPP daily threshold) from approximately 16.2% in 2011–12 to 2.3% by 2022–23, with rural areas driving the decline from higher baselines. Independent estimates applying the Rangarajan method to the 2022–23 Household Expenditure Survey (HCES) suggest a headcount ratio around 26.4%, though critics argue low thresholds and potential underreporting in surveys may inflate the pace of decline. Shifting to multidimensional poverty indices (MPI), NITI Aayog's assessments using (NFHS) data show a steeper reduction, with the MPI headcount falling from 24.85% in 2015–16 to 14.96% in 2019–21, equating to over 13.5 people exiting multidimensional . Extending this framework, government projections claim a further drop to 11.28% by 2022–23, lifting 24.82 individuals, attributed to improvements in health, education, and living standards indicators. These MPI figures, while capturing non-income deprivations, face scrutiny for assuming uniform weighting across dimensions and potential in self-reported NFHS data, contrasting with slower consumption-based trends.
Year/PeriodMethodologyNational Headcount Ratio (%)Key Notes/Source
2004–05Tendulkar37.2NSSO consumption survey baseline.
2011–12Tendulkar21.9Last major NSSO round; rural focus.
2011–12Rangarajan29.5Higher thresholds for essentials.
2015–16 to 2019–21MPI (NFHS)24.85 to 14.96Multidimensional deprivations halved.
2022–23Extreme ($2.15 PPP)~2.3–5.3World Bank/estimates; data gaps noted.
These measured reductions align with economic growth post-1991 liberalization and targeted interventions, though debates persist on whether data discontinuities and methodological shifts overstate progress relative to verifiable consumption gains.

Causal Factors in Declines

Sustained has been the primary driver of in , with empirical studies demonstrating a strong inverse relationship between GDP growth rates and poverty headcount ratios. Higher growth accelerated declines in poverty by boosting opportunities and real wages, particularly in the post-1991 era when annual GDP growth averaged around 6-7%, contributing to a drop in the rural poverty rate from approximately 37% in 2004-05 to under 10% by 2019-21 according to -based measures. This causal link is evidenced by growth elasticities of poverty reduction, where a 1% increase in correlates with a 2-3% decline in poverty incidence, driven by expanded labor market participation rather than redistribution alone. A key mechanism underlying this growth-induced decline has been the rise in labor earnings, especially for unskilled workers, fueled by demand from expanding sectors like and services. Between 2004-05 and 2011-12, unskilled wages increased by over 6% annually in real terms, accounting for much of the observed as households shifted from to higher-productivity non-farm jobs. Rural non-farm employment growth, including factory-based activities, further supported this by absorbing surplus agricultural labor and raising household incomes, with studies attributing up to 40% of rural poverty decline to such structural shifts. to areas and associated remittances also played a significant role, enhancing living standards in sender households by supplementing local earnings during the . Government welfare schemes have supplemented these market-driven factors by stabilizing among vulnerable populations, particularly through direct transfers that mitigated shocks and supported short-term poverty alleviation. Programs such as the National Food Security Act, providing subsidized grains to over 800 million people, contributed to a sharp post-2011 decline in from 27.1% to 5.3% by 2022-23, as measured by PPP $2.15 benchmarks, by boosting caloric intake and freeing up household budgets for other essentials. Schemes like MGNREGA provided rural wage employment, increasing labor income during agricultural lean periods and aiding poverty resilience, though their impact on long-term declines remains secondary to overall growth, with evaluations showing limited effects on . However, while these interventions correlate with gains at the bottom quintile, independent analyses caution that they primarily redistribute rather than generate new productivity, with sustained declines hinging more on expansion than state outlays. Declines in multidimensional poverty indices, incorporating health and education alongside income, further reflect combined effects of growth and targeted policies, with a 10% reduction in multidimensional deprivation linked to 3-4% higher per capita income growth from 1998-2021. Urbanization and infrastructure improvements have amplified these trends by facilitating market access and skill upgrading, though uneven regional distribution—faster declines in states like versus —highlights the primacy of local investment climates over uniform scheme coverage. Overall, while schemes buffered vulnerabilities, empirical evidence underscores that poverty contraction stems fundamentally from enhanced productive capacities rather than transfer dependency.

Criticisms and Systemic Flaws

Identification Errors and Exclusions

Identification of households below the poverty line (BPL) in frequently results in substantial errors of exclusion, where genuinely poor families are denied eligibility, and errors of , where non-poor households receive benefits. A in a tertiary care hospital setting found that among 374 respondents, over 69% of those classified as poor lacked BPL cards, while 5.5% of above-poverty-line individuals possessed them, highlighting systemic targeting inaccuracies in provisioning. Similarly, analyses of the Public Distribution System (PDS) indicate exclusion errors affecting nearly 61% of eligible households and errors impacting 25%, driven by flawed survey processes and verification gaps. Exclusion errors often stem from rigid, non-geographically adjusted criteria in BPL censuses, such as the exercise, which automatically disqualified households based on assets like mechanized farming equipment without accounting for regional economic realities, leading to widespread omission of rural poor. The 2011 Socio-Economic and Caste Census (SECC) perpetuated these issues through imprecise scoring and low data quality, with automatic exclusion rules failing to capture transient or deprived subpopulations overlooked by consumption-based metrics like the Tendulkar methodology, which critics argue understates living costs and nutritional needs. Recent administrative reforms, including AI-driven verification in , have exacerbated exclusions by erroneously delisting thousands of legitimate beneficiaries due to algorithmic mismatches in family databases and outdated income thresholds. In , as of October 2025, technical gaps and obsolete income norms—unchanged since —risk further sidelining poor households amid crackdowns on bogus cards, prioritizing inclusion purges over accurate verification. Inclusion errors arise primarily from and lax enforcement during BPL surveys, as seen in the 2002 , where allowed affluent households to secure cards, inflating beneficiary lists and diverting resources. These inaccuracies persist due to reliance on self-reported data without robust cross-checks, enabling false claims in schemes like PDS, where ineligible urban or asset-owning families exploit loopholes. Methodological critiques, including those of the Tendulkar line's calorie-centric approach, indirectly contribute by setting thresholds that fail to differentiate true deprivation, allowing borderline non-poor to qualify amid verification failures. Overall, such errors undermine program efficacy, with exclusion disproportionately harming the most vulnerable—often landless laborers or seasonal migrants—while erodes fiscal sustainability, as evidenced by persistent debates over data reliability in official estimates.

Leakages, Misuse, and Corruption

Leakages in India's Public Distribution System (PDS), which primarily targets Below Poverty Line (BPL) households for subsidized food grains, have historically diverted substantial resources from intended beneficiaries. Estimates indicate that PDS leakages—defined as the proportion of allocated grains not reaching households—stood at approximately 42% in 2011-12 but declined to 22-28% by 2022-23, reflecting partial improvements from and biometric authentication. Despite this, annual leakages amount to about 20 million tonnes of subsidized grains, equivalent to a fiscal loss of ₹69,000 , often through diversion to open markets or waste. Earlier econometric analyses across 20 states from 2004-2012 reported average leakages of 36.4%, with BPL-specific diversions at around 30% in 2011-12, exacerbated by opaque allocation processes and low beneficiary awareness. Misuse of BPL identification manifests in inclusion errors, where ineligible households obtain cards, undermining . A study at a major public hospital in found that 5.5% of above-poverty-line (APL) patients held BPL cards, enabling non-poor access to subsidies intended for the destitute. Nationwide audits have revealed systemic issuance of fake or ineligible cards; for instance, over 1.17 potentially unqualified ration cards were flagged for removal under the National Food Security Act, while state-level drives cancelled more than 10 ineligible BPL cards in one instance and 2.75 in Haryana alone. These errors stem from subjective criteria in BPL surveys, political influence in card distribution, and inadequate verification, allowing affluent or deceased individuals' households to retain benefits. Corruption within BPL-linked schemes often involves between officials, dealers, and intermediaries, facilitating beneficiaries and black- sales. In PDS operations, leakages are driven by under-reporting of offtake, with grains siphoned at fair-price shops for resale at market rates; a 2005 government evaluation estimated that only ₹1 of every ₹3.65 spent reached BPL households. Such practices persist despite reforms, as evidenced by observations on unscientific BPL classification enabling misuse and excluding genuine poor families from subsidies. Empirical studies attribute higher leakages to reduced accountability in non-targeted Above Poverty Line () allocations spilling over to BPL streams, with state variations showing at a low 0.3% leakage versus national averages due to stricter monitoring. Overall, these issues highlight causal failures in decentralized implementation, where local incentives favor over delivery, though technological interventions have mitigated but not eliminated the problem.

Over-Reliance on State Intervention

The Below Poverty Line (BPL) identification system underpins a wide array of state-subsidized entitlements in , including food grains via the Public Distribution System (PDS), housing assistance, and cash transfers, which collectively impose escalating fiscal demands on government budgets. In financial year 2024-25, total subsidies are forecasted to surpass budgeted allocations by reaching Rs 4.1-4.2 lakh crore, driven partly by targeted outlays that crowd out investments in , , and job creation. This resource misallocation is compounded by explicit subsidies' role in inflating state-level deficits, with some analyses attributing up to a significant portion of fiscal stress to populist expansions tied to BPL targeting. Such heavy dependence on state intervention risks entrenching a culture, where benefit eligibility cliffs—loss of subsidies upon crossing thresholds—discourage labor force participation and enhancement among recipients. Econometric studies of welfare schemes indicate that subsidies can generate work disincentives, aligning with the broader " trap" hypothesis that transfers reduce incentives for or formal work, thereby perpetuating poverty cycles despite short-term relief. Targeted programs like those under BPL exacerbate this through exclusion errors and opaque recertification, where households under-report earnings to retain access, undermining long-term . Critics, including policy analysts, argue that this model shifts focus from structural reforms—such as skill development and liberalization—to handout-based palliatives, fostering inefficiency and political over sustainable growth. Historical policy evolution shows a pivot from growth-oriented industrialization in the early post-independence era to welfare-heavy approaches post-1990s, correlating with persistent rural despite scheme expansions. distortions from subsidized , like fertilizers linked to BPL agrarian , further hinder gains, as resources are funneled into rather than productive assets. While proponents cite immediate deprivation mitigation, empirical fiscal trajectories reveal vulnerabilities: rising public from subsidy overhangs limits counter-cyclical responses, as evidenced by states like and facing subsidy-induced fiscal slippages exceeding 3% of GDP.

Reforms and Future Directions

Technological and Administrative Updates

The Indian government has mandated the seeding of numbers with ration cards for Below Poverty Line (BPL) beneficiaries under the National Food Security Act (NFSA), enabling biometric authentication and electronic (eKYC) processes to verify eligibility and curb ghost beneficiaries. As of July 2025, this initiative targets over 800 million NFSA beneficiaries, with states required to complete validation against the Unique Identification Authority of India (UIDAI) database to ensure accurate distribution of subsidized food grains. The process involves point-of-sale () devices at fair price shops for iris or fingerprint scans, which have facilitated (DBT) of subsidies, reducing leakages by linking payments directly to authenticated Aadhaar-enabled accounts. Administrative reforms include the expansion of the One Nation One Ration Card (ONORC) scheme, fully implemented nationwide by 2023, allowing BPL migrants to access entitlements across state borders via -based portability. States must periodically update BPL lists through online portals like the , incorporating mechanisms and to address exclusions or inclusions based on verified data. For health-related entitlements, the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY) leverages the 2011 Socio-Economic and Caste Census (SECC) database to automatically enroll SECC-identified BPL families, with digital health IDs under the (ABDM) integrating for paperless claims processing since its 2021 launch. These updates aim to enhance targeting precision amid criticisms of outdated SECC data, though implementation varies by state, with northern regions showing higher seeding rates above 90% by mid-2025. Ongoing UIDAI advisories emphasize 100% validation to prevent misuse, supported by apps for self-verification.

Debates on Abandoning Fixed Poverty Lines

Critics of fixed absolute lines argue that these thresholds, defined by a static real-value basket of basic , fail to adapt to and societal changes, potentially underestimating ongoing deprivations once extreme is alleviated. In developing economies, where aspirations and social norms evolve, fixed lines may declare eradicated prematurely while relative income gaps persist, exacerbating perceptions. Advocates for retaining fixed lines, including economists like Martin Ravallion, emphasize their utility in measuring subsistence-level hardship and enabling cross-country comparisons, particularly in low-income settings where caloric intake dominates welfare concerns. Relative measures, often set at 40-60% of , risk rendering poverty thresholds negligible in the poorest nations, obscuring absolute gains from interventions like food subsidies or . In , the debate has intensified with the government's pivot toward the National Multidimensional Poverty Index (MPI), which discards singular fixed monetary cutoffs in favor of weighted deprivations across health, education, and living standards, drawing from National Family Health Surveys. The MPI headcount ratio declined from 24.85% in 2015-16 to 14.96% in 2019-21, reflecting reductions in indicators like sanitation access (from 58% deprived to 19%) and years of schooling. This shift addresses limitations of prior fixed lines, such as the 2011 Tendulkar Committee's ₹27 daily rural threshold (adjusted for inflation), criticized for excluding non-income hardships amid rapid . Yet detractors note MPI's reliance on periodic household surveys introduces data lags and subjective weighting, potentially inflating in monetary terms where surveys show under 5% below national lines in 2022-23. Hybrid proposals, combining absolute floors with relative adjustments, have gained traction globally, as seen in the World Bank's 2022 update elevating lines to $2.15 while adding $3.65 and $6.85 benchmarks for middle-income contexts. In , some analysts propose raising thresholds beyond $2.15, arguing it has outlived utility given negligible rates below 1% by 2022-23, to better target residual vulnerabilities without fully jettisoning fixed metrics.

Integration with Caste Enumeration

The Indian government initiated efforts to integrate Below Poverty Line (BPL) identification with caste enumeration through the Socio-Economic and Caste Census (SECC) 2011, approved by the Union Cabinet in May 2011 to coincide with the planned BPL census from June to December that year. This exercise aimed to collect household-level socio-economic data, including caste and religion details, to replace the exclusionary binary BPL system with a deprivation-based ranking for more precise welfare targeting, particularly in rural areas where automatic exclusion criteria (e.g., owning a pucca house or mechanized farm equipment) were applied without direct caste input in scoring. However, while caste data was canvassed via questionnaires alongside 48 socio-economic indicators, the final deprivation index for beneficiary selection deliberately omitted caste as a scoring factor to avoid reinforcing identity-based divisions, focusing instead on empirical markers of deprivation like access to education, housing, and assets. Implementation revealed significant challenges in data quality and utilization, with the Registrar General of reporting in 2016 that approximately 98% of the collected caste data was error-free, yet full national release of caste-wise figures was withheld due to inconsistencies, duplication, and logistical issues in enumeration. Rural SECC data, released in 2015 by the Ministry of Rural Development, informed revisions to BPL-like lists for schemes such as the National Rural Employment Guarantee Act (MGNREGA) and housing programs, enabling states to prioritize the poorest households within caste categories for sub-allocation of quotas, but urban data and comprehensive caste-poverty intersections remained unpublished. A 2017 parliamentary panel recommended leveraging SECC deprivation scores to expand BPL coverage beyond traditional income thresholds, indirectly incorporating caste insights for , though federal reluctance persisted amid concerns over politicization. Ongoing debates highlight the potential for enhanced integration via a national , as demonstrated by Bihar's 2023 state-level survey, which enumerated alongside economic indicators to reveal disproportionate among certain backward castes (e.g., 42.93% of Extremely Backward Classes below versus 27.13% overall), informing targeted sub-quotas. Proponents, including opposition parties post-2024 elections, argue that linking enumeration to metrics would enable evidence-based redistribution, addressing intra- inequities where upper echelons benefit disproportionately from reservations, but critics caution against data inaccuracies exacerbating exclusion errors, as seen in prior BPL surveys where only 29% of cardholders were verifiably poor per findings. Government policy under the has favored releasing only aggregated socio-economic data from SECC to prioritize universal deprivation over -specific lines, reflecting a causal emphasis on economic indicators amid fears of deepened social fragmentation. As of 2025, proposals for the 2027 decennial to include enumeration could revive integration efforts, potentially refining BPL successors like the by intersecting with verified deprivation data from sources such as the .

References

  1. [1]
    PERCENT OF POPULATION LIVING BELOW POVERTY LINE
    (b) Brief Definition: The proportion of the population with a standard of living below the poverty line. (c) Unit of Measurement: %. (d) Placement in the ...
  2. [2]
    Half of the global population lives on less than US$6.85 per person ...
    Dec 8, 2022 · 648 million people in the world, about eight percent of the global population, live in extreme poverty, which means they subsist on less than US$2.15 per day.
  3. [3]
    Federal Poverty Level (FPL) - Glossary | HealthCare.gov
    A measure of income updated yearly by the Department of Health and Human Services (HHS) that's used to determine eligibility for certain programs and benefits.
  4. [4]
    What does living at the poverty line look like in the US? - USAFacts
    For an individual, the poverty threshold is $14,891. The US Department of Health and Human Services (HHS) issues its poverty guidelines based on the Census ...<|separator|>
  5. [5]
    How the Census Bureau Measures Poverty
    Apr 9, 2025 · If a family's total income is less than the family's threshold, then that family and every individual in it is considered in poverty. The ...
  6. [6]
    The Poverty Line Matters, But It Isn't Capturing Everyone It Should
    Mar 5, 2020 · The calculation doesn't take into account housing, transportation, child care, or medical costs. It doesn't consider geographical differences, ...
  7. [7]
    International Poverty Line: Definition, Criticism, Uses - Investopedia
    Criticism of the International Poverty Line. Using the international poverty line to determine how well off a population is can be misleading, as the line ...
  8. [8]
    Where in the world do the poor live? It depends on how poverty is ...
    Aug 2, 2023 · The international poverty line, currently set at $2.15, is the standard metric for monitoring extreme poverty in the world. This standard is ...
  9. [9]
    Poverty Estimating system in India - Vskills Blog
    The first was group was WORKING GROUP 1962. It recommended that the national minimum consumption expenditure should be Rs.20 per capita per month in rural areas ...
  10. [10]
    Poverty estimation in India - PRS India
    ... poverty line of Rs 75 per capita per year. Post independence poverty estimates: In 1962, the Planning Commission constituted a working group to estimate poverty ...
  11. [11]
    Poverty Estimation in India - Levelup IAS
    Nov 30, 2023 · In 1962, Planning commission formed a Working Group to estimate poverty nationally. ... Commission's suggestion of Rs 27 a day as poverty line ...
  12. [12]
    Poverty Estimation in India - Drishti IAS
    Oct 10, 2019 · VM Dandekar and N Rath (1971), made the first systematic assessment of poverty in India, based on National Sample Survey (NSS) data. Unlike ...<|control11|><|separator|>
  13. [13]
    Poverty estimation in India - PRS India
    Aug 20, 2021 · VM Dandekar and N Rath made the first systematic assessment of poverty in India in 1971, based on National Sample Survey (NSS) data from 1960-61 ...
  14. [14]
    (PDF) History of Defining Poverty and Poverty Line: A Debate for the ...
    History of Defining Poverty and Poverty Line: A Debate for the Economic Development in India ; decided on the basis of the overall incidence of income poverty ...Missing: conceptualization 1947
  15. [15]
    Poverty estimation in India - PRS India
    History of poverty estimation in India Pre independence poverty estimates ... Post independence poverty estimates: In 1962, the Planning Commission ...
  16. [16]
    Poverty Estimation in India - BYJU'S
    Alagh Committee (1979)​​ The Taskforce constituted by the Planning Commission under the direction of YK Alagh, constructed a poverty line for rural and urban ...
  17. [17]
    Below Poverty Line (BPL) Census to be conducted along with Caste ...
    May 19, 2011 · The first BPL Census was conducted in 1992 for the eighth five year plan. Subsequently, BPL census was conducted in 1997, for the Ninth five ...
  18. [18]
    Identification and Classification of BPLs in India - Planning Tank
    Jul 11, 2020 · The first attempt was made during the Eighth five year plan in 1992 ... Appraisal of BPL Criteria, New Delhi: Ministry of Planning.
  19. [19]
    [PDF] The Public Distribution System in India (1939-2001)
    In June 1997, the government introduced the targeted PDS (TPDS) where a distinction was made between people who were living below the poverty line (BPL) and ...
  20. [20]
    [PDF] OPHI Working Paper
    In 1992, at the beginning of the 8th five-year plan, the identification of BPL households was based on self-reported income data. A household was identified as ...
  21. [21]
    [PDF] Additional Essential Factors for Considering the "Below Poverty ...
    Jul 30, 2014 · BPL Identification in 2007​​ As per 11th five year plan, new parameters had been designed and changed the entire questionnaire as comparison with ...
  22. [22]
  23. [23]
  24. [24]
    India's Declining Poverty Figures Based on Flawed Estimation method
    A person living at the official 2009-10 poverty lines would have been able to consume 1880 calories in rural areas and 1720 calories in urban areas.
  25. [25]
    [PDF] NATIONAL MULTIDIMENSIONAL POVERTY INDEX - NITI Aayog
    Jul 17, 2023 · This report, National. Multidimensional Poverty Index (MPI): A Progress Review 2023 (based on NFHS-5) is a significant update to its baseline ...
  26. [26]
    Below Poverty Line | Full Form of BPL, History and Benefits
    Aug 28, 2023 · Then in 2012, the poverty line in rural India was ₹972; in urban India, it was ₹1,407. During that time, according to reports about 29.5% of ...
  27. [27]
    Poverty in India: The Rangarajan Method and the 2022–23 ...
    The Expert Group (2014) method defines the poverty line as the sum of expenditure on essential non-food items of the median (45–50th) fractile, the expenditure ...
  28. [28]
    [PDF] Measuring Multidimensional Poverty in India: A New Proposal ...
    Sep 2, 2008 · 3.1 2002 BPL Methodology​​ The 2002 rural BPL census comprises thirteen questions for each household, covering topics such as food, housing, work ...
  29. [29]
    Socio Economic and Caste Census (SECC) 2011 - Department of ...
    SECC-2011 is a study of socio economic status of rural and urban households and allows ranking of households based on predefined parameters. SECC 2011 has three ...
  30. [30]
    [PDF] identification of BPL families
    Jul 30, 2015 · The aggregate score of a household could range from a minimum of zero to a maximum of 52. The households were arranged in ascending order to ...
  31. [31]
    [PDF] National Multidimensional Poverty Index
    India's national MPI measure uses the globally accepted and robust methodology developed by the. Oxford Poverty and Human Development Initiative (OPHI) and the ...
  32. [32]
  33. [33]
    [PDF] OPHIWORKING PAPER NO. 54 - Identifying BPL Households A ...
    Finally, we show how state-level. BPL poverty caps vary if they reflect multiple deprivations in variables – such as malnutrition and housing – through a ...
  34. [34]
  35. [35]
    Identifying BPL Households: A Comparison of Methods | OPHI
    This paper empirically examines the proposed Socio-Economic Caste Census (SECC) methodology and compares it with alternative proposals.
  36. [36]
    National Food Security Act, (NFSA) 2013
    The identification of beneficiaries by States/UTs is a continuous process ... Corresponding to the all India coverage of 75% and 50% in the rural and urban ...
  37. [37]
    Implementation of National Food Security Act (NFSA)
    The National Food Security Act, 2013 (NFSA) provides for coverage of upto 75% of the rural and 50% of the urban population, at the all India level.
  38. [38]
    Why the Government Relies on SECC Data Instead of a Poverty ...
    Oct 28, 2016 · The government is hoping to use the multi-dimensional SECC data for identifying beneficiaries in more schemes while retaining a poverty line in India to track ...
  39. [39]
    SECC Excludes More Than It Includes Amidst High Rural Distress
    Aug 9, 2015 · 56 percent of rural households are landless (ownership of land less than 0.01 hectare); 51 percent are dependent on unskilled manual labour for ...
  40. [40]
    [PDF] BPL criteria
    criteria for the Socio Economic Caste Census (SECC), 2011 for collecting information on socio economic indicators. The criteria for rural and urban areas ...
  41. [41]
    Identifying BPL households : a comparison of methods - ORA
    This paper empirically examines the proposed Socio-Economic Caste Census (SECC) methodology and compares it with alternative proposals. Using variables in ...
  42. [42]
    [PDF] India's National Food Security Act (NFSA): Early Experiences
    Jun 24, 2017 · According to Section 10(1b) of NFSA, State Governments were required to identify eligible households. “within such period not exceeding three ...
  43. [43]
    Ration Card in India 2025: Types, Eligibility & Benefits | Motilal Oswal
    May 13, 2025 · 3. State BPL (Below Poverty Line) Ration Card · Eligibility: Total family income below ₹10,000 to ₹20,000 per month (varies by state). Should not ...Missing: 2023-2025 | Show results with:2023-2025
  44. [44]
  45. [45]
    Public Distribution System (PDS) - NFSA
    The Public Distribution System (PDS) evolved as a system of management of scarcity through distribution of foodgrains at affordable prices.
  46. [46]
    FAQs | Official Website of Department of Food and Public ...
    What is the Targeted Public Distribution System? · What is the AAY scheme? · What is the procedure for obtaining BPL/AAY/APL ration card? · How much quantity of ...<|separator|>
  47. [47]
  48. [48]
    Rashtriya Swasthya Bima Yojana - National Portal of India
    Jul 4, 2016 · RSBY has been launched by Ministry of Labour and Employment, Government of India to provide health insurance coverage for Below Poverty Line (BPL) families.
  49. [49]
    National Family Benefit Scheme - myScheme
    Eligibility. The applicant must be a citizen of India. The family of the applicant must be living Below Poverty Line (BPL). The primary breadwinner of the ...
  50. [50]
    Pradhan Mantri Garib Kalyan Anna Yojana (PMGKAY)
    Apr 19, 2024 · The provision of free food grains under PMGKAY for next five years with effect from 1 st January 2024 reflects the long-term commitment and ...Missing: benefits | Show results with:benefits
  51. [51]
    BPL - Below Poverty Line: Complete Guide - (2025) - PayMe
    Jan 22, 2025 · History of “Below Poverty Line” in India. In India, the concept of the Below-Poverty Line (BPL) has evolved over the decades as the country ...
  52. [52]
    [PDF] India: Trends in Poverty, 2011-12 to 2022-23 - Methodology Note
    May 6, 2025 · The previous estimate published in the PIP—based on imputations and URP data—was 12.92 percent for 2021. • Poverty calculated under the LMIC ...
  53. [53]
    Small area variations in four measures of poverty among Indian ...
    Jan 17, 2023 · This paper examined the 2019–2021 National Family Health Survey to examine small area variations in four measures of household poverty.
  54. [54]
    [PDF] BPL variations in States
    The BPL Census 2011 is underway to identify the people Below Poverty line (BPL) based on a self-declaration of respondents in response to the criteria finalized ...
  55. [55]
    Poverty estimation in India - PRS India
    The percentage of the population living below the poverty line in India decreased to 22% in 2011-12 from 37% in 2004-05, according to data released by the ...
  56. [56]
    [PDF] Press Note on Poverty Estimates, 2011-12 Government of India ...
    Jul 22, 2013 · Since the data from the NSS 68th round (2011-12) of Household. Consumer Expenditure Survey is now available, and the Rangarajan Committee ...
  57. [57]
    Beyond Statistics, is Poverty Actually Reducing in India? - The Wire
    May 3, 2025 · Interestingly, while the Tendulkar method estimated poverty at 21.9% in 2011-12, the Rangarajan method placed it at 29.5%. This discrepancy ...
  58. [58]
    [PDF] Reassessing India's Poverty Decline over the Missing Decade - LSE
    Feb 3, 2025 · It critiques two major attempts to estimate poverty during this time: one using national account growth rates and the other using a private ...
  59. [59]
    Has Poverty Declined in India? The World Bank Believes So
    Jul 15, 2025 · The World Bank estimates that India's extreme poverty has declined from 16.2 per cent in 2011-12 to 2.3 per cent in 2022-23.Missing: critiques | Show results with:critiques
  60. [60]
    Publication: Poverty in India Has Declined over the Last Decade But ...
    Extreme poverty in India decreased by 12.3 percentage points from 2011 to 2019, with greater rural reductions, but urban poverty rose in 2016.Missing: critiques | Show results with:critiques
  61. [61]
    Measuring Poverty in India : A Report - FAS
    Dec 19, 2024 · This resulted in an overall poverty head-count ratio of 26.4%. “Using a low poverty line threshold, that too in data that possibly contains ...
  62. [62]
    India. National Multidimensional Poverty Index: A Progress Review ...
    Dec 11, 2023 · It provides multidimensional poverty estimates for India's 36 States and Union Territories, along with 707 administrative districts across 12 indicators of the ...
  63. [63]
    24.82 crore Indians escape Multidimensional Poverty in last 9 years.
    Jan 15, 2024 · MPI's global methodology is based on robust Alkire and Foster (AF) method that identifies people as poor based on universally acknowledged ...
  64. [64]
    Assumptions Matter: Revisiting India's Multidimensional Poverty Index
    Jan 14, 2025 · The NITI Aayog (2023) in its report on the National Multidimensional Poverty Index (MPI) estimates that 13.5 crore people in India moved out ...
  65. [65]
    Unpacking the data: Why India's poverty decline may not be what it ...
    Jun 19, 2025 · Poverty is falling but mind the hype. There is clear evidence that poverty has declined in India. But overstating the extent of this fall by ...
  66. [66]
    India reduces extreme poverty to 5.3% in 2022-23 - Facebook
    Jun 9, 2025 · India has made significant strides in reducing extreme poverty, with the rate plummeting from 27.1% in 2011-12 to 5.3% over a decade.
  67. [67]
    [PDF] Reducing Poverty in India: The Role of Economic Growth
    We provide evidence that higher growth rates were associated with faster decline in poverty, partly because growth helped increase employment and real wages ...
  68. [68]
    India eliminates extreme poverty - Brookings Institution
    Mar 1, 2024 · Poverty: High growth and large decline in inequality have combined to eliminate poverty in India for the PPP$ 1.9 poverty line.
  69. [69]
    [PDF] Defining and Explaining Inclusive Growth and Poverty Reduction; by ...
    Our results suggest that economic growth has been a major driver of poverty reduction and inclusiveness in India. While positive distributional changes aided.
  70. [70]
    Publication: Why Did Poverty Decline in India?
    The results show that poverty decline is associated with a significant increase in labor earnings, explained in turn by a steep rise in wages for unskilled ...
  71. [71]
    [PDF] How Does Poverty Decline? - UCR | Department of Economics
    Their empirical results show that much of the growth in the rural non- farm sector in India was due to the rural factory sector and not due to the non-traded.
  72. [72]
    Extreme poverty in India sees sharp decline! Number dips from ...
    Jun 7, 2025 · A recent World Bank report indicates a significant decline in extreme poverty in India, dropping from 27.1% to 5.3% between 2011-12 and 2022-23.
  73. [73]
    government welfare schemes spur consumption and income ... - PIB
    Jan 31, 2025 · Evidence shows that government schemes have spurred consumption and income generating activity in low-income households, observes the Economic Survey.
  74. [74]
    [PDF] Growth, Urbanization and Poverty Reduction in India
    Using data up to the early 1990s, Ravallion and Datt (1996) found that rural economic growth was more poverty reducing, as was growth in the tertiary. (mainly ...<|separator|>
  75. [75]
    Multidimensional poverty and growth: Evidence from India 1998–2021
    We explore the growth effects of multidimensional poverty in India from 1998 to 2021. A 10% decrease in poverty increases per capita income by approximately 3– ...
  76. [76]
    [PDF] Growth, Structural Change, and Poverty Reduction
    The snapshot indicates that while growth in India has been associated with an unambiguous decline in poverty, the extent of poverty reduction in India has been ...
  77. [77]
    Errors of inclusion and exclusion in income-based provisioning of ...
    Among the 374 study subjects, more than 69% of poor did not possess a BPL card. On the other hand, 5.5% of the above poverty line patients among the respondents ...
  78. [78]
    [PDF] Detection of False Income Level Claims Using Machine Learning
    Feb 8, 2022 · A Study [18] has shown that Public Distribution System suffers from nearly 61% of error in exclusion and 25% of error in inclusion of ...Missing: census | Show results with:census<|separator|>
  79. [79]
    Did You Know About the BPL Census (Part I)?
    Jul 13, 2011 · The exclusion criteria did not allow any geographical variations. For example, one of the exclusion criteria was whether the household operated ...Missing: false positives negatives
  80. [80]
    How an algorithm denied food to thousands of poor in India's ...
    Jan 24, 2024 · It adopted AI in welfare schemes to weed out ineligible ones, but has wrongfully removed thousands of legitimate ones.
  81. [81]
    Technical gaps, outdated income norms put Karnataka's poor at risk ...
    Oct 2, 2025 · Technical gaps, outdated income norms put Karnataka's poor at risk of BPL exclusion. The State government has intensified its crackdown on bogus ...Missing: positives negatives
  82. [82]
    [PDF] Targeting with Agents - UC San Diego Department of Economics
    BPL cards are India's most important targeting mechanism; participation in a wide range of public schemes, including the Tar- geted Public Distribution System ( ...
  83. [83]
    A methodology deeply flawed - The Hindu
    Feb 5, 2010 · A methodology deeply flawed. The poverty line that the Tendulkar Committee proposes depends on reduced calorie consumption, and fails to provide ...Missing: identification | Show results with:identification
  84. [84]
    Identification of the Poor: Errors of Exclusion and Inclusion
    Feb 26, 2011 · This paper tries to estimate the extent of inclusion and exclusion errors in the identification of below-thepoverty line households.Missing: Poverty | Show results with:Poverty
  85. [85]
    Declining PDS leakages: A look at the numbers - Ideas for India
    Aug 11, 2025 · Estimates have shown that leakages of foodgrain from the Public Distribution System declined from 42% in 2011-12 to 22-28% in 2022-23.
  86. [86]
    PDS leaks costing exchequer Rs 69000 crore a year: Report
    Nov 18, 2024 · A new study reveals that nearly 28% of India's subsidized grains, intended for the poor, are lost to leakage, costing the government an ...
  87. [87]
    [PDF] Leakage and Corruption in India's Public Distribution System
    In this paper I investigate econometrically how leakage in the PDS, which I define as the proportion of grain supplied to the System not reaching beneficiaries, ...
  88. [88]
    Ration Crackdown: Centre's data sweep finds over 1 Crore ineligible ...
    about 1.17 crore — may not qualify for free food grains under the National Food Security Act ...
  89. [89]
  90. [90]
    2.75 lakh BPL cards cancelled in month-long clean-up drive
    May 12, 2025 · The number of BPL ration cardholders dropped from 51.97 lakh in April to 49.22 lakh, a nearly 5% reduction, according to Aadhaar-enabled data ...
  91. [91]
    Plugging PDS Pilferage: A Study of an SMS-based Monitoring Project
    A 2005 study estimates that for every Rs 3.65 spent by the Government of India, only Re 1 reaches BPL households (PEO 2005). There is a very contentious ...
  92. [92]
    SC questions 'scientific' basis of BPL classification, flags misuse of ...
    Mar 20, 2025 · Concerns were raised about deserving families not receiving essential subsidies due to misuse and improper distribution of ration cards, ...
  93. [93]
    At .3 per cent, Telangana's PDS leakage lowest in India
    Nov 19, 2024 · Telangana has recorded the lowest leakage percentage of grains of 0.3 per cent from the Public Distribution System (PDS), while Gujarat stood in the third ...Missing: estimates | Show results with:estimates
  94. [94]
    Government's subsidy burden to exceed budget estimates to Rs 4.2 ...
    Jan 24, 2025 · Government's subsidy burden is expected to rise to about Rs Rs 4.1-4.2 lakh crore in the financial year 2024-25 (FY25) more than the budget estimates of Rs 3.8 ...
  95. [95]
    Government subsidy burden to exceed budget, likely to hit Rs 4.2 ...
    Jan 24, 2025 · India Business News: The government's subsidy burden for FY25 is ... subsidies, which are likely to overburden the budgeted allocation.
  96. [96]
    State subsidy burden is straining India's fiscal health - ThePrint
    Mar 19, 2025 · ... India (RBI, 2022). In this context, the growing burden of explicit subsidies is particularly concerning. Explicit subsidies – direct ...Missing: disincentives | Show results with:disincentives
  97. [97]
    Rationalizing Subsidies in India - Drishti IAS
    Jan 15, 2025 · Fiscal Strain and Resource Misallocation: Government subsidies place a heavy burden on public finances, often diverting resources from ...
  98. [98]
    An Econometric Analysis of Welfare Schemes and Labor Force ...
    Aug 12, 2025 · The global discourse on social welfare is dominated by the "dependency trap" hypothesis, which posits that subsidies disincentivize work.Missing: BPL evidence
  99. [99]
    Do subsidies and safety nets take focus away from generating jobs?
    Subsidies and safety nets can lead to a culture of dependency, where people become reliant on government handouts instead of seeking employment opportunities.<|separator|>
  100. [100]
    Identification of BPL Households for Poverty Alleviation Programs
    Aug 6, 2025 · Five-Year Plan (1997-2002 concluded that replacing the PDS might not be acceptable, despite the systemic inefficiencies in the current system. .
  101. [101]
    'Freebies' and Welfare Schemes: Setting a Framework for the ...
    Feb 16, 2023 · Rather than relying on social welfare schemes, the Nehru government placed its bets on industrialisation. It relied on increased agricultural ...
  102. [102]
    [PDF] Declining Clientelism of Welfare Benefits? Targeting and Political ...
    It has been argued that under the BJP-led central government, welfare benefits in. India have become more programmatic, less prone to clientelistic control by ...
  103. [103]
    [PDF] Freebies and Subsidies in India: Are They Leading to Fiscal ... - IJFMR
    Jul 17, 2025 · The study highlights the fiscal burden caused by freebies, which contribute to rising public debt, budget deficits, and market distortions.Missing: disincentives | Show results with:disincentives
  104. [104]
    Fiscal burden of subsidies triggers political debate, rethink on freebies
    Nov 5, 2024 · Political parties routinely make pre-poll promises of subsidies and freebies, but the fiscal burden of such guarantees weighs heavily on state ...
  105. [105]
    [PDF] Nationwide implementation of e-KYC procedure for beneficiaries ...
    that all ration cards/beneficiaries' data is seeded with their Aadhaar numbers and also validated with UIDAI. 55. All States/UTs are being regularly advised ...
  106. [106]
    Aadhaar authentication of 800M ration beneficiaries underway
    Jul 1, 2025 · The Indian government is accelerating digital authentication or eKYC of more than 800 million National Food Security Act (NFSA) beneficiaries who will receive ...Missing: integration | Show results with:integration
  107. [107]
    Aadhaar Usage - Unique Identification Authority of India
    This page intend to provide information about various Aadhaar based developmental and public beneficial initiatives and programs.
  108. [108]
    Ration Card Dashboard - NFSA
    Know your ration card status, common registration facility (CRF), district food and supply offices, toll free helpline numbers in states, online grievance.
  109. [109]
    Homepage | Ayushman Bharat, Haryana | India
    SECC identified families are covered in Ayushman Bharat Scheme. All members of eligible families as present in SECC database are automatically covered. PMJAY ...State · Comprehensive Cashless... · PM-JAY · Contact<|control11|><|separator|>
  110. [110]
    India's Poverty Story Transformed - PIB
    Jun 7, 2025 · Improved methods captured more actual spending, leading to a more realistic poverty line and a lower poverty rate despite the increase in ...
  111. [111]
    Another Good Reason to Dislike Low-Bar Global Poverty Lines
    Aug 27, 2014 · There is a second very big problem with low poverty lines, one less remarked upon. The use of low poverty lines dramatically understates the ...
  112. [112]
    A Relative Question - Finance & Development, December 2012
    Low- and middle-income countries have tended to favor absolute lines, while most high-income countries have preferred relative lines. Richer countries also tend ...
  113. [113]
    [PDF] Absolute and Relative Poverty Measurement - World Bank Document
    In a nutshell, the idea behind relative poverty measures is that relative economic position is the key determinant of welfare and not the absolute economic ...
  114. [114]
    National Multidimensional Poverty Index: A Progress Review 2023
    The National Multidimensional Poverty Index: A Progress Review 2023 provides multidimensional poverty estimates for India's 36 States & Union Territories, along ...
  115. [115]
    Poverty debates in India - The Indian Express
    Oct 17, 2024 · According to the Household Consumption Expenditure Survey for 2022-23, less than 5 per cent of Indians are now expected to live below the poverty line.
  116. [116]
    [PDF] Tracing The Evolution Of Poverty Measurement In India
    The origin of poverty line estimation in India dates back to 1901 when Dada Bhai Naoroji made the earliest attempt during the pre-independence era. He estimated ...
  117. [117]
    The Sharp Decline in India's Poverty - ORF America
    Feb 5, 2025 · First, India has virtually eliminated extreme poverty, defined as people living below $1.9 per day (adjusted for purchasing power parity or PPP) ...Missing: abandoning fixed<|separator|>
  118. [118]
    Centre to seek caste, religion details during BPL survey | India News
    May 19, 2011 · The Centre is set to canvas "caste and religion" with questionnaires to find the poor in the upcoming BPL census, likely to start in July. While ...
  119. [119]
    Cabinet approves caste and BPL census - Governance Now
    It would help identify the proportion of every religion and caste among the BPL category. While the BPL data for urban and rural poor would be utilised for ...
  120. [120]
    98% of the caste data is error-free: Registrar General and Census ...
    Sep 27, 2021 · 98% of the caste data is error-free: Registrar General and Census Commissioner of India told parliamentary panel in 2016. Error is not in data ...
  121. [121]
    Tap Census deprivation data to revise, expand BPL: Panel to Govt
    Jan 14, 2017 · While the rural data of SECC was released by the ministry in 2015, the urban and the caste data were never made public by the government, a ...<|separator|>
  122. [122]
    Caste Census in India: Need and Challenges - Drishti IAS
    May 7, 2025 · The Tendulkar Committee (2009) found that 29% of below poverty line (BPL) cardholders are poor, while 13% of Above Poverty Line (APL) ...
  123. [123]
    HT Explainer: Why the 2011 caste data was not made public?
    Aug 29, 2024 · The key objectives of the exercise were to rank households based on their socioeconomic status and get authentic information on caste-wise ...