National Sample Survey Organization Research Articles

Estimating poverty for India after 2011 using private-sector survey data

The last expenditure survey released by India’s National Sample Survey organization dates back to 2011, which underpins the last official estimates of poverty and inequality. This paper adopts a new approach to estimate India’s poverty and inequality trajectory since 2011 using a newly available household panel survey conducted by the private sector. The results suggest that (1) extreme poverty is estimated to be lower in 2019 than in 2011, with greater poverty reductions likely in rural areas, and (2) coinciding with the demonetization event, urban poverty likely rose in 2016. The results should not be interpreted as definite proof. While the estimated trends in poverty sit well with a range of corroborative evidence, significant uncertainty remains stemming from sampling and non-sampling errors associated with the private-sector survey.

Income Elasticity of Demand for Healthcare and Change Over Time: Across the Income Groups in India

The study computes the income elasticity of out-of-pocket healthcare expenditures (OOPEs) of Indian households across the income groups. Using data from the National Sample Survey Organization for the 71st (2014) and 75th (2018) rounds, a log-linear model with splines estimates the elasticity of healthcare expenditure across different income segments. The analysis controls for demographic variables and employs dual deflation to adjust for price changes. The elasticity magnitude depends upon the marginal propensity to OOPE (MP-OOPE), which is inconsistent across the income groups. The random MP-OOPE is due to the non-linear relationship between income and healthcare expenditure. The data revealed increased income (proxied by household consumption expenditure) and decreased average OOPE in wave 2. Despite this, households in the bottom income bracket experience a rise in elasticity, and those at the top observe reduced elasticity in wave 2. The income group-wise MP-OOPE suggests uncertain healthcare demand patterns and evidence of widening healthcare inequality. Poorer households either face low-magnitude inelastic healthcare demand, leaving their healthcare needs unmet, or experience high-magnitude inelastic demand, leading to financial hardship. Policies should aim to reduce out-of-pocket healthcare expenses for vulnerable groups. Expanding public-funded risk pooling mechanisms like Pradhan Mantri Jan Arogya Yojana would be crucial in addressing this issue.

A decompositional analysis of social group inequality in India

ABSTRACT Using the national representative Indian household surveys collected by the National Sample Survey Organization, we examine the welfare gaps across social groups for the entire distribution in 1983, 1993–94, 2004–05 and 2011–12. We use spatially adjusted per capita consumption expenditure as the measure of welfare and show that there exists significant welfare gap between Scheduled Tribes/Scheduled Castes (ST/SC) and General Category (GC) households at higher quantiles of the distribution, but the magnitude of the gap has declined over the years for the SC households. Using unconditional quantile regression decomposition, we find that the coefficient effect (unexplained effect) dominates the endowment effect (explained effect) in explaining the gap in all four years. Further decomposition shows that the difference in educational distribution between the SC/ST and GC households drives most of the explained differences between the social groups.

Detection of outliers in survey–weighted linear regression

ABSTRACT Regression diagnostics help identify influential data points in a model. Detecting outliers in complex survey design data involving stratification, clustering, and unequal probability sampling is difficult due to the presence of masking, where one outlier makes it hard to detect others. The masking factor for survey–weighted linear regression is developed and applied to analyzing the Household Consumer Expenditure dataset of 68th round of the National Sample Survey Organization survey of India. Regression parameters are calculated before and after detection and removal of outliers. The standard error of regression parameters for survey-weighted least squares models is reduced by 2% for the intercept, 5% for variable “meat” (X 5), 4% for “served processed food” (X 9), and 4% for “packaged processed food” (X 10). Inference alters the significance of regression coefficients of the variable “served processed food” (X 9) leading to the emergence of significance. There is no change in inference for other variables.

Gender Conundrum and Unpaid Work in India: Empirical Evidence from India’s First Large-scale Time Use Survey

The study was aimed at (a) exploring the anomalies in conceptualising and measuring work, especially that of the women, (b) analysing the patterns of unpaid work distribution between men and women, and (c) examining the drivers of time spent on unpaid work in India. It has been argued that the under-conceptualisation of work and the methodological constraints led to invisibilising several activities, mostly performed by girls and women, in the prevailing labour force statistics and national income accountings. We have noted that such anomalies could be overcome with the advancement of robust statistical tools like that of time use survey. By employing the first and the most recent pan time use survey, conducted by the National Sample Survey Organization across the country in 2019, we have assessed the gender patterns of unpaid work and its determinants. We found the existence of a stark gender gap both in terms of participation and average time spent on unpaid work across rural and urban regions. Again, the findings, obtained through the Tobit regression model, reveal that the nature of the association and the extent of time allocated to unpaid work vary substantially across the demographic and socio-economic characteristics. JEL Codes: J22, J21, J40, J46, C10

Decomposing the inequalities in the catastrophic health expenditures on the hospitalization in India: empirical evidence from national sample survey data.

Sustainable Development Goal (SDG) Target 3.8.2 entails financial protection against catastrophic health expenditure (CHE) by reducing out-of-pocket expenditure (OOPE) on healthcare. India is characterized by one of the highest OOPE on healthcare, in conjunction with the pervasive socio-economic disparities entrenched in the population. As a corollary, India has embarked on the trajectory of ensuring financial risk protection, particularly for the poor, with the launch of various flagship initiatives. Overall, the evidence on wealth-related inequities in the incidence of CHE in low- and middle-Income countries has been heterogenous. Thus, this study was conducted to estimate the income-related inequalities in the incidence of CHE on hospitalization and glean the individual contributions of wider socio-economic determinants in influencing these inequalities in India. The study employed cross-sectional data from the nationally represented survey on morbidity and healthcare (75th round of National Sample Survey Organization) conducted during 2017-2018, which circumscribed a sample size of 1,13,823 households and 5,57,887 individuals. The inequalities and need-adjusted inequities in the incidence of CHE on hospitalization care were assessed via the Erreygers corrected concentration index. Need-standardized concentration indices were further used to unravel the inter- and intra-regional income-related inequities in the outcome of interest. The factors associated with the incidence of CHE were explored using multivariate logistic regression within the framework of Andersen's model of behavioral health. Additionally, regression-based decomposition was performed to delineate the individual contributions of legitimate and illegitimate factors in the measured inequalities of CHE. Our findings revealed pervasive wealth-related inequalities in the CHE for hospitalization care in India, with a profound gap between the poorest and richest income quintiles. The negative value of the concentration index (EI: -0.19) indicated that the inequalities were significantly concentrated among the poor. Furthermore, the need-adjusted inequalities also demonstrated the pro-poor concentration (EI: -0.26), denoting the unfair systemic inequalities in the CHE, which are disadvantageous to the poor. Multivariate logistic results indicated that households with older adult, smaller size, vulnerable caste affiliation, poorest income quintile, no insurance cover, hospitalization in a private facility, longer stay duration in the hospital, and residence in the region at a lower level of epidemiological transition level were associated with increased likelihood of incurring CHE on hospitalization. The decomposition analysis unraveled that the contribution of non-need/illegitimate factors (127.1%) in driving the inequality was positive and relatively high vis-à-vis negative low contribution of need/legitimate factors (35.3%). However, most of the unfair inequalities were accounted for by socio-structural factors such as the size of the household and enabling factors such as income group and utilization pattern. The study underscored the skewed distribution of CHE as the poor were found to incur more CHE on hospitalization care despite the targeted programs by the government. Concomitantly, most of the inequality was driven by illegitimate factors amenable to policy change. Thus, policy interventions such as increasing the awareness, enrollment, and utilization of Publicly Financed Health Insurance schemes, strengthening the public hospitals to provide improved quality of specialized care and referral mechanisms, and increasing the overall budgetary share of healthcare to improve the institutional capacities are suggested.

Do hospitalizations push households into poverty in India: evidence from national data.

High percentage of OOP (Out-of-Pocket) costs can lead to poverty and exacerbate existing poverty, with 21.9% of India's 1.324 billion people living below the poverty line. Factors such as increased patient cost-sharing, high-deductible health plans, and expensive medications contribute to high OOP costs. Understanding the poverty-inducing impact of healthcare payments is essential for formulating effective measures to alleviate it. The study used data from the 75th round of the National Sample Survey Organization (Household Social Consumption in India: Health) from July 2017-June 2018, focusing on demographic-socio-economic characteristics, morbidity status, healthcare utilization, and expenditure. The analysis included 66,237 hospitalized individuals in the last 365 days. Logistic regression model was used to examine the impact of OOP expenditures on impoverishment. Logistic regression analysis shows that there is 0.2868 lower odds of experiencing poverty due to OOP expenditures in households where there is the presence of at least one child aged 5 years and less present in the household compared to households who do not have any children. There is 0.601 higher odds of experiencing poverty due to OOP expenditures in urban areas compared to households in rural areas. With an increasing duration of stay in the hospital, there is a higher odds of experiencing poverty due to OOP health expenditures. There is 1.9013 higher odds of experiencing poverty due to OOP expenditures if at least one member in the household used private healthcare facility compared to households who never used private healthcare facilities. In order to transfer demand from private to public hospitals and reduce OOPHE, policymakers should restructure the current inefficient public hospitals. More crucially, there needs to be significant investment in rural areas, where more than 70% of the poorest people reside and who are more vulnerable to OOP expenditures because they lack coping skills.

Morbidity transition at the national and sub-national level and their determinants over the past and contemporary period in India.

The study delves into the epidemiological transition, examining the intricate changes in health status patterns and their connection to morbidities. Specifically, it assesses morbidity transition at both national and subnational levels in India and their determinants from 1995 to 2018. This study examines self-reported morbidities in India by utilising four rounds of National Sample Survey Organisation (NSSO) data (52nd, 60th, 71st, and 75th) from 1995-2018. We estimated prevalence by conducting descriptive analysis on socio-demographic determinants and morbidities such as: Infectious and Communicable Diseases (In&CDs), Non-communicable diseases (NCDs), Disability and other diseases. Moreover, we employed pooled regression analysis to explore morbidity risk transitions over the past decades. The study revealed a steady upsurge in morbidity prevalence in India, doubling from 56 (per thousand) in 1995 to 106 in 2014. However, a considerable decline was observed in the most recent round in 2018 (79 per thousand). From 1995 to 2018, NCDs gained a prominent share in morbidity trends. Kerala in the southern region reported the highest rates, followed by states like Lakshadweep, Andhra Pradesh, Karnataka, West Bengal, Punjab, and others. Age, sex, residence, education, caste, religion, and wealth are pivotal factors in determining the severity of different disease burdens in different sections of the population in India. Over the study period (1995, 2004, 2014, and 2018), the odds of reported morbidities risk transition significantly increased over successive decades: 1.81 times in 2004 (95% CI: 1.78-1.84), 2.16 times in 2014 (95% CI: 2.12-2.2), and 1.44 times in 2018 (95% CI: 1.41-1.46), compared to 1995 (52nd round). The study reveals significant disparities in morbidity reporting across Indian states from 1995 to 2018, attributed to distinct demographic, social, and economic determinants. India continues to grapple with the dual burden of diseases, but the NCDs burden is mounting at a faster pace than CDs.

Distribution and Usage of Digital Payment Cards in India: Findings from NSS 77th Round Survey

Promoting digital economy is a policy priority of the Government of India. The latest available large-scale survey data on households’ debt and investment from National Sample Survey Organization (NSSO, 2021) provides details on the possession and utilization of payment cards for adults across India. Using the information, this article explores the state and district-level variations in its distribution and usage in India—which is a crucial knowledge gap in the existing literature. The article finds that while 85% of Indian adults have a bank account, less than half of them have a debit or credit card. Also, 82% of card-holders have actually used their cards for transactions during 365 days prior to the survey. Access to payment cards seems crucial for digital integration. This article attempts to identify policy handles that can help in the spread of payment cards. Their possession is aggregated at district levels and regressed on several indicators. The article identifies that literacy rate, access to banking, road density, prevalence of Self-Help Groups and Co-operative Credit Societies are all significant positive influencers towards digital integration. A similar result is obtained for the usage of payment cards as well. This article comes up with a first glimpse of digital integration at the pan-India level while also providing some policy suggestions for enhancing cashless transactions in India.

Magnitude of health expenditure induced removable poverty in India: Some reflections of Ayushman Bharat

The authors have measured the health expenditure-induced removable poverty in India using nationally representative consumer expenditure surveys of three quinquennial rounds conducted by the National Sample Survey Organization (NSSO). This study has also focused on the reflections of Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), the world's largest Government-funded health insurance scheme, on these poverty rates in the country. The study has used headcount, payment gap, and concentration index to measure the economic burden and impoverishment impact of out-of-pocket (OOP) health expenditure. The analysis shows that the incidence and depth of poverty are substantially understated because of overlooking OOP health expenditure in the country's standard poverty measure. Outpatient care contributes almost four times more than inpatient care to health expenditure-induced impoverishment in India, though this care has not been covered in the AB-PMJAY. Muslims, among all religious groups, Scheduled Castes among social groups, and casual labourers among different household types are more vulnerable to OOP health expenditure-induced removable poverty in the country. Poverty, in general, has dropped significantly, but the share of health expenditure-induced poverty in general poverty has increased substantially. It has risen considerably in rural areas and among India's most vulnerable sections of society in the past 20 years. We emphasised that universal health insurance coverage is needed in India. Implementing comprehensive health insurance schemes that cover both inpatient and outpatient care can help alleviate the financial burden of healthcare expenses on households and contribute to reducing poverty rates.

Pattern and drivers of profitability in India’s unorganised manufacturing sector

Using data from National Sample Survey Organisation surveys, the paper analyses the profit rate and its drivers in India’s unorganised manufacturing sector for the period 2000–01 to 2015–16. The entire period has been subdivided into three smaller periods to examine the short-run fluctuations in profitability. The study has been carried out at disaggregate level, namely, state and industry levels as well. The output-capital ratio has behaved cyclically over the years, whereas a steady rise in the profit share has been the driver of cyclically rising profit rate over the period. A rapid growth in labour productivity with a non-commensurate rise in wage rate has been the reason behind the rise in profit share. The ranking of states and industries on profit rate has been found to be relatively unchanged.

If you can't fix the problem change the standards.

Over the last few months, established data systems in India have been the target of heated dispute, chiefly by members of the Economic Advisory Council to the Prime Minister, ranging from the inflation numbers [1], to the sampling frame for surveys done by the National Sample Survey Organisation (NSS), the National Family Health Survey (NFHS) and the Periodic Labour Force Survey (PLFS)[2], haemoglobin cut-offs for anaemia [3] and childhood growth standards, female labour force participation rate and life expectancy at birth [4]. The attempts to revise economic data systems has invited a raging debate [5, 6], prompting the government to set up a panel to review the NSS's methodology. However, the arguments being made in favor of downward revision of nutritional standards have received much less scrutiny, except for a recent editorial which comments on the general problem of drawing up standards [7]. This is despite the fact that these proposals have already caught the fancy of the government. A policy decision has already been taken to discontinue gathering of data on Hb-levels as part of the quinquennial National Family Health Surveys, which would now be collected as part of a new Dietary and Bio-markers Survey. Neither the rationale for such a move, nor the details of the methodology of the new survey, or the time-frame within which such data would be released have been made available for public deliberation. Similarly, discussions have been initiated on devising "indigenous" growth standards for children [8]. Hence, it becomes imperative to examine the basis of these renewed calls for revision of existing standards.

Structural Change, Services Sector and Intergenerational Occupational Mobility in India: Some Exploratory Evidence

This study investigates into intergenerational occupational mobility of Indian workers towards and within service sectors during globalization. In particular, such mobility of workers is observed in the presence of structural shift of the economy towards service industry, especially towards service trade, and explores whether there is intergenerational mobility towards services and more ­skill-oriented occupations in India during 1999–2011. The Altham measure of relative mobility is applied on the National Sample Survey Organization employment–unemployment survey database to measure the degree of association between occupational choice of fathers and co-resident sons in urban India. An upward mobility among sons is observed between 1999–2000 and 2011–2012. JEL Codes: F14, F16, J62, L80, C46

Need for living wages in India: Case studies of agricultural workers in rural Madhya Pradesh

AbstractThe present study discusses the current wage situation in India and the need for living wages as workers and employees grapple with the cost of living crisis. A case study of two districts of Madhya Pradesh (MP) state is presented to demonstrate how the living wage benchmarks based on the Anker Methodology compare with existing minimum wage fixations and other development indicators. The living wage benchmarking is based on field surveys conducted in Ratlam and Chhindwara districts in October–December 2021, and a rigorous analysis of nationally representative consumption and expenditure surveys conducted by the National Sample Survey Organisation and the Centre for Monitoring Indian Economy. Our living wage estimates are 1.8 times the minimum wages for agricultural labourers and 43% more than those earned by non-agricultural unskilled labourers. Moreover, the actual wages reported are less than half of the estimated living wages, indicating that the current incomes and wages for workers and farmers of rural MP are far from adequate to lead a decent life.

Access and Uses of ICTs: Can Virtual Learning Be an Alternative Mode of Education in India?

This study analyses household access and persons’ uses of information and communication technologies (ICTs) in India by using the latest National Sample Survey Organization’s (NSSO) Education survey (2017–2018) datasets. Accordingly, an ICT Index is computed, and a logistic model is applied to examine the pattern and likelihood of digital technology usage and access. The result shows that access to ICTs is lower in rural areas and access increases with the level of education. The study also observes that factors like education, income and regional variations are significant aspects of the disproportionate uses and access of ICTs at the household and individual levels. This study also observed that the low level of access to ICTs will be a huge challenge for the Government to ensure alternate online or virtual modes of education.

Impact of Low Birth Weight on the Prevalence and Economic Burden of Common Childhood Illnesses Among Under-Five Children in India: Findings From Nationally Representative Surveys.

Background Common childhood illnesses such as diarrhea, fever, and acute respiratory infection impose substantial health burdensamong under-five children, and Low Birth Weight (LBW) has been associated with an increased prevalence of these illnesses. However, the impact of LBW on healthcare utilization and the economic burden of these illnesses remains understudied. Aim To assess the impact of LBW on the prevalence, healthcare utilization, and Out of Pocket Expenditure (OOPE) for outpatient (OP) treatment of selected Common Childhood Illnesses(CCHI) among under-five children in India. Methodology This study utilized data from two nationally representative surveys conducted in India; National Family Health Survey (NFHS-5) (2019-2021) and the National Sample Survey Organization (NSSO) 75th Round Schedule Social Consumption: Health (2017-2018). Data from the NFHS-5 was analyzed to assess the impact of LBW on the prevalence of selected CCHI and healthcare utilization. Comparison of OOPE for OP treatment of selected CCHI between LBW and Normal Birth Weight (NBW) children done using the median OOPE for OP visits of CCHI estimated from the NSSO data. Results The two-week prevalence of selected CCHI among LBW and NBW children was found to be 20.0% (95% CI19.6 -20.4) and 18.0% (95% CI 17.8 -18.2), respectively. There was no significant difference between LBW and NBW children on healthcare utilization for the treatment of CCHI; both groups had a similar proportion (around 70%) of formal medical treatment utilization for CCHI. The median OOPE spending for OP visits per episode of CCHI was comparable between LBW and NBW children. However, families of LBW children had higher annual OOPE spending for OP visits related to CCHI, with projected estimates of INR 1,446 ($19.56) for LBW children and INR 1,271 ($17.2) for NBW children. Conclusion LBW was associated with a higher prevalence of CCHI. Even though healthcare utilization was similar among LBW and NBW children, a higher prevalence of CCHI among LBW children led to higher OOPE. LBW children have approximately 13% higher annual OOPE spending for the OP visits related to selectedCCHI compared to NBW children.

Long-term health and human capital effects of in utero exposure to an industrial disaster: a spatial difference-in-differences analysis of the Bhopal gas tragedy

ObjectivesGlobalisation and industrialisation can increase economic opportunity for low/middle-income nations, but these processes may also increase industrial accidents and harm workers. This paper examines the long-term, cohort-based health effects of...

Access and Determinants of Formal Agriculture Credit In Uttar Pradesh, India

The study has attempted to examine the determinants of formal agricultural credit in rural Uttar Pradesh using National Sample Survey Organisation data from the 70th round (2012–13). The Binary Logistic Regression (BLR) model is used to examine the determinants of formal credit in Uttar Pradesh. Socio-economic and demographic characteristics such as age, gender, social group, and family size are grouped into social, economic, and extension services. The findings from this study revealed that indebtedness exists and that almost 45 per cent of farmers have taken credit from informal credit agencies. Further, there is significant heterogeneity in terms of socio-economic and demographic features among farmers who have taken credit from formal and informal credit agencies. The BLR results show that gender, literacy rate, operated area, bank account, livestock, and Kisan Credit Card are key social and economic determinants of formal credit in rural Uttar Pradesh. The calculated odds ratio shows a 2.008 times higher probability of literate male farmers taking a loan from formal credit than others. Likewise, there is a 3.10 times higher probability of taking formal credit if farmers follow technical advice provided by agricultural universities, NGOs, and scientists through open-source platforms. Hence, the following policies are suggested to deal with indebtedness: (i) Policymakers can choose to intervene in the rural credit lending system by liberalising policy to more accurately reflect the characteristics of potential borrowers and in light of their current borrowing strategies, (ii) the BLR results depict a positive relationship with land size, and agricultural households with larger land seem to get more benefits. Therefore, the government should focus on marginal and small farmers, who have larger shares in the total operational landholdings, (iii) safety net programmes like the Public Distribution System (ration cards), in the presence of formal credit, may induce farmers and their families to increase their per capita monthly consumption expenditures, and (vi) State intervention is also required in terms of increasing the size of livestock, as this can be an area where Uttar Pradesh can lead the other States as this will help in diversification in the field of agriculture .

Strengths-based Gram Sabhas? Challenges and radical possibilities when ‘measuring’ poverty in India

Poverty as an object of study in India continues to be the domain of economists, statisticians and demographers. The National Sample Survey Organisation (NSS) serves as the main instrument of data collection to measure poverty relative to economic indicators. In this paper we draw on strengths-based research undertaken in an Indian village to foreground alternative ways of conceptualising and practising data collection when measuring poverty. Explored through an analytics of biopolitics, asset-mapping exercises with young people and women revealed new subjectivities that emerged via illustrative meaning-making and dialogue. This approach to poverty measurement facilitated methods and produced outcomes that were less calculated and predefined than the NSS, and encouraged participation, even questioning of the status quo, in the ‘doing’ of the methodology itself. A strengths orientation to poverty opens up radical possibilities, particularly in India where the state-sanctioned self-­governing body, the Gram Sabhas, has a mandate to provide for the most marginalised groups. And while this governing body is not free from power imbalances, the potential it offers, when combined with strengths-based approaches (SBA) that value people for the expertise they already have, demands renewed attention in practitioner and policy debates in the country.

Falling Between the Cracks: Women’s Work and the Periodic Labour Force Survey

This article reflects upon the changes introduced in the Periodic Labour Force Survey (PLFS) and their impact on the visibility of women’s work in India. In 2017–2018, the National Sample Survey Organisation’s five-yearly employment–unemployment surveys (EUS) were replaced by the annual PLFS, and in the transition, the section that comprised probing questions was dropped. These questions had been introduced in 1972–1973 to highlight women’s productive activities, which otherwise remain invisible. The section was key to collecting information on not only women’s reproductive work but also the unrecognised productive work women undertake within the walls of their homes. It provided a window in a society where women’s work is underestimated as well as unappreciated.