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This paper tries to investigate the question of whether the poverty ratio across Indian states is converging in the post-2000s. We addressed this question of spatial convergence of the poverty ratio using unconditional convergence over the period 2004–05 to 2018–19 for 18 major states of India, considering both rural and urban regions. We used the unit-level data of NSSO’s Consumer Expenditure Surveys (CES) for the 61st, 68th and PLFS 2018–19 rounds for the analysis. Besides, we try to assess the driving factors of poverty through a panel regression model. The results reveal that in the first period from 2004–05 to 2011–12, Indian states experienced a divergence in the overall poverty ratio and rural poverty. However, the second period, 2011–12 to 2018–19, witnessed no specific trend of convergence or divergence across states. Again, in the case of urban poverty, there is no particular pattern of poverty convergence or divergence during both periods. The study shows that the Gini coefficient, educational expenditure, household size, infant mortality, literacy rate, MPCE, primary-sector income and per capita power availability are the significant determinants of poverty in India. [ABSTRACT FROM AUTHOR]

Tamil Nadu is one of India's most agriculturally developed states, but has high-income inequality and indebtedness among its farmers. This study explores the dynamics of farm indebtedness among farmers in the Cauvery Delta Zone of combined Tamil Nadu state and Puducherry Union Territory. Resonating with the state-level trend, income inequality among the sampled farm households is significantly high, with a Gini coefficient of 0.56, and it decreases with an increase in farm size. Similarly, 80% of farmers are indebted, with the incidence of indebtedness, extent of indebtedness and proportion of institutional loanees increasing with farm size. Though all categories of farmers have considerable access to institutional credit, large farmers can fulfil all their credit needs through institutional sources, while small landholders have to fulfil almost 30% of their credit needs through non-institutional sources. Elderly farmers, large landholders and farm households with more dependent members are more prone to indebtedness than their counterparts, while farm households earning more income and possessing more assets are less prone to indebtedness. Various production, weather, market and institutional constraints deter farmers from repaying their outstanding loans, resulting in a vicious cycle of indebtedness. Therefore, farmers and youth of small farm households should improve their alternative employment opportunities by utilizing the state-sponsored skill development programmes and enhance their financial accessibility by availing Kisan Credit Cards. [ABSTRACT FROM AUTHOR]

The present paper studied the impact of educational inequality on child mortality in the states of southern region of India during the period 1991 to 2019. The study applied the Gini coefficient technique to investigate the education inequality in each state of the region. The paper observed the highest educational inequality in Andhra Pradesh while the lowest in Kerala among the states. However, such educational inequality is highest in the rural areas as compared to the urban areas in each state. The improvement of the average years of schooling contributed to the reduction of education inequality in the region. The study observed that the reduction of education inequality leads to the growth of per capita NSDP in each state of the region. Similarly, the expansion of education sector leads to reduction of child mortality rate in each state of the region. [ABSTRACT FROM AUTHOR]

The study estimates household poverty by using state specific poverty line for rural and urban sectors separately, as defined by Tendulkar Methodology and estimates logistic regression for identifying the determining factors of household poverty. Taking advantage of Household Consumption Expenditure Data from the 61st (2004-2005) and 68th (2011-2012) round of the National Sample Survey, the study estimates regional level household poverty and consumption expenditure across socio-religious groups in India. In addition, the study measures household consumption expenditure and inequality by using Gini coefficient and Lorenz curves at regional level and among different socio-religious groups in India. We find that the poverty level has declined by 15.52 per cent between 2004-2005 and 2011-2012. Meanwhile across social groups, the Scheduled Caste and Scheduled Tribes households are comparatively poorer than Other Backward Classes and Others category households. Similarly, in terms of household consumption expenditure inequality, there is no significant difference in the value of Gini ratio and Lorenz curve of Monthly Per capita Consumption Expenditure between the rounds but they diverge towards the end. [ABSTRACT FROM AUTHOR]

The objective of this research study is to compare the performance of and test the reliability of four accounting-based models on a sample of 30 companies under the Insolvency and Bankruptcy Code in India and a matched sample of 30 solvent companies. The solvent companies are identified as those with highest and high safety, denoted with credit ratings ‘AAA’ and ‘AA’, respectively, and are matched on size (market capitalisation), year, and sector. The four models chosen are: Altman original Z-score, Altman Z-score for emerging markets, Ohlson model, and Zmijewski model. The scores are computed for T−1, T−2, and T−5 years, where T is the year the company filed under the IBC. The research findings reveal that all the models are able to predict default accurately for one and two years prior to bankruptcy, but fail to do so accurately for T−5 years. The predictive ability of the models is evaluated by ROC curves and the Gini coefficient. It is observed that the Ohlson model has the highest predictive ability, followed by the Zmijewski model and the Altman Z-score. In the next stage of our analysis, we compare the four accounting-based models with the Merton (market-based) model and the logit model to assess if the models, in their original form, are more accurate than these two models for the Indian markets. It is observed that the Merton model has the highest predictive accuracy, followed by Ohlson, Zmijewski and Altman Z-score. We conclude that neither the accounting nor the market models in themselves are sufficient; the models need to be reassessed based on specific regions and industries, and the scores need to be re-computed for better accuracy. We recommend that for accurate and early prediction, we need to look beyond financial statements to qualitative and other quantitative variables, so that defaults can be preempted and lenders be forewarned against impending distress. [ABSTRACT FROM AUTHOR]

This study analyses the dynamics of consumption inequality among various occupational groups using household survey data from National Sample Survey (NSS). Three rounds of NSS data namely, the 50th (1993–1994), 61st (2004–2005), and 66th (2009–2010) were taken for the purpose of analysis. Various measures such as Gini coefficient, overlapping index, and raking matrices are estimated for the whole as well as the subgroups using ANOGI methodology. From the analysis, it is found that the level of overall inequality as well as the between‐group inequality is on the rise during the period of analysis. Further, the measures such as relative overlap index and ranking matrices give conclusive evidence that the difference between various groups in terms of consumption expenditure pattern is increasing over time. From the ranking matrices, it is seen that the last six groups, constituting households with occupation in the unorganized sector and low level organized workers falls below the 30th percentile of consumption expenditure distribution of the first group groups that consists of individuals holding to technical, administrative, managerial, and executive occupations. Worsening inequality across various occupational groups is a matter of concern, especially from the policy perspective. As economic growth without equitable distribution of income is not a desirable outcome. [ABSTRACT FROM AUTHOR]

The Sustainable Development Goal (SDG) Target 10 aims at reducing inequalities in different aspects. The Niti Aayog of India has been monitoring progress achieved by different states and sets out a collaborative agenda. This paper specifically looks at the trends in Gini coefficient in different states, impact of high-income inequality on index of health in developed economies and how political ideology and progressive taxation policy can play a decisive role in thwarting the present disturbing trends. The paper brings out how income share of the 40% middle class in national GDP has come down after economic liberalization, while the share of top 10% has gone up significantly. In developed countries, acute income inequality seems to dampen the index of health and general well-being. The paper looks at Kuznet's inverted U curve hypothesis, which contends that after achievement of a high level of per capita income, inequality will come down, was proved to be un-true by Thomas Piketty. The paper brings out, how the Laffer Curve (1986) mooted by Arthur Laffer provided the economic justification for bringing down tax rate on top rich from 71% to 35% in the USA. The paper rebuts the general assumption that high tax rates would disincentive investment. The author recognizes that substantial increase in tax rates and high wealth tax in a market oriented political economy may not be a feasible proposition. In order to achieve distributive justice, greater attention to tools like progressive taxation, increasing investment in merit goods and ensuring shared prosperity must be seriously addressed. Also, a more proactive approach towards tax collection, rather than increasing borrowing would help to reduce income inequality. [ABSTRACT FROM AUTHOR]

We examine the trends in inequality in length of life in India and fifteen of its selected states during the last three decades. We also estimate the contribution of mortality change in different age groups to the overall change in inequality in length of life in India and selected states of India. We assess the Gini coefficient, life disparity, and threshold age to examine the inequality. Finally, we decompose the change in the Gini coefficient into contributions of mortality change in different age groups. In Indian males, the life expectancy at birth increased by about 8 years between 1981 and 2011. The life disparity decreased by 3.6 years and the threshold age increased by 5.5 years during this period. In Indian females, the life expectancy increased by about 12 years, the life disparity reduced by 5.2 years, and the threshold age increased by 7.2 years. Mortality changes in 0–1 contributed most to the decline in Gini between 1981 and 2011 for males, females, and urban residents. Further, mortality change in 1–4 contributed most to the decrease in Gini in rural residents. Changes in various measures of mortality pattern differ markedly between males and females, urban-rural residents, and states of India. [ABSTRACT FROM AUTHOR]

The north-eastern region of India presents intra-regional disparity, which is reflected in every aspect of development. The transport sector, especially railway transportation, is one of the important aspects, and the development of railway infrastructure seems to be very different in every region. The research question addressed in this study was "Which factors, geo-physical or socio-economic, influenced the variation in the level of railway development in Northeast India?" The aim of the study was to delineate regional differentiation on railway development in Northeast India and to analyse the reasons for different development patterns of railway lines among the north-eastern states. The research was based on secondary data collected from multiple sources, and the existing synthetic indicator was applied for the classification of eight states based on their railway infrastructural status. An alternative approach called the alternative synthetic indicator has been proposed and found to be more efficient than the existing synthetic indicator. The degree of inequality among the northeastern states by considering railway infrastructural variables was measured by plotting a Lorenz curve; the corresponding Gini coefficient specifies the unequal distribution of railway infrastructure among all the northeastern states. The causality of such unequal development has been analysed through a correlation test by defining the composite dimension index. The analysis revealed that all the externalities of regional inequality significantly influence the development of railway lines in northeastern states. Environmental determinism plays a crucial role in railway development in Northeast India, but political willingness is also crucial for creating an actual state of differentiation and will play a special role in the future. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the convergence in per-capita income (measured as per-capita net state domestic product) of regions in India during the period 1990–1991 to 2017–2018. Two separate analyses have also been done for the sub-periods, i.e., 1990–1991 to 2003–2004 and 2004–2005 to 2017–2018, to find out the effect of the second phase of economic liberalization in India. Design/methodology/approach: In a panel data study, the estimation of absolute and conditional beta (β)-convergence and sigma (σ)-convergence across 17 Indian regions have been done. To measure the dispersion of per-capita income across the regions in India, the standard deviation of logs, Gini coefficient, Mehran measure, Piesch measure, Kakwani measure and Theil index have been estimated. In addition to this, these indices have been regressed over time. Findings: This study finds the presence of absolute and conditional β-convergence; the regions with low initial per-capita income have grown faster than the regions with high initial per-capita income. Further, this study finds that foreign direct investment (FDI) inflow and the availability of power enhance growth across regions. However, this study finds the presence of σ-divergence, which indicates that the economic inequality among the regions in India has widened over the periods, calling for policy interventions to promote growth in the backward regions through the promotion of FDI inflow and the availability of power. Originality/value: This study highlights the rising economic inequality among the regions in India by analyzing the latest available data through appropriate econometric techniques. [ABSTRACT FROM AUTHOR]

Objective: Despite operational guidelines, anecdotal evidence suggests that newborn vitamin K1 prophylaxis is not practiced routinely in India. This study determined the coverage of vitamin K1 prophylaxis among newborns in the country.Design: Nationwide cross-sectional data on live births and newborns receiving vitamin K1 during the 2019-2020 reporting period were abstracted from the Health Management Information System (HMIS). The coverage estimates of newborn vitamin K1 prophylaxis were derived nationally and also for individual states and union territories (UT). Additionally, coverage heterogeneities were investigated using classifiers, viz. geography, socio-demographic index (SDI), special developmental categories and institutional birth rate (IBR).Setting: India.Participants: 20 208 804 newborns documented with HMIS.Results: Vitamin K1 was administered to overall 62·36 % newborns (95 % CI: 62·34 to 62·38 %). The Central zone (49·0 %), low SDI states (54·39 %), Empowered Action Group states (53·32 %) and states with low IBR (44·69 %) had the lowest coverage amongst their respective groupings. Across the individual states and UT, the coverage ranged widely from 22·18 % (in Tripura) to 99·38 % (in Puducherry), exhibiting considerable variability (coefficient of variation: 33·74 %) and inequality (Gini coefficient: 0·17). While the coverage in eight states/UT (i.e. Arunachal Pradesh, Manipur, Nagaland, Tripura, Uttar Pradesh, Uttarakhand, Telangana and Andaman & Nicobar Islands) was below 50 %; only five states/UT (i.e. Chandigarh, Gujarat, Goa, Puducherry and Tamil Nadu) achieved above 90 % coverage.Conclusion: Vitamin K1 prophylaxis was not practiced in more than one-third newborns in India. It calls for identifying the barriers, addressing the gaps and implementing newborn vitamin K1 prophylaxis more effectively throughout the country. [ABSTRACT FROM AUTHOR]

This article assesses the nexus between land and income inequality among agricultural households in rural India based on a national survey of farmers. The study also assesses the contribution of other sources of income to this inequality. At the onset, we estimate the extent of land and income inequality using the Gini coefficient, Palma ratio, and quantile distribution. Further, we examine the effects of income components and sociodemographic, production theory‐related, and geographic variables on total income inequality among agricultural households at the national level using regression‐based inequality decomposition (RBID) analysis of income function. The evidence indicates that both land and income inequality are the maximum in the agriculturally developed states. The results of RBID show that land size explains the highest share of income inequality among agricultural households, followed by crop productivity at the household level. The analysis further statistically validates that the share of wage and livestock income has an inverse relationship with total inequality among agricultural households. These results provide firm empirical evidence to assess policies suggested to increase alternative sources of income among land‐poor petty producers. [ABSTRACT FROM AUTHOR]

This study presents the first in-depth analysis of spatial differences and factors influencing wealth distribution among households in India. It uses data from the latest National Family Health Survey, covering 707 districts. Techniques like the Lorenz curve, Gini coefficient, Location Quotient, Morans statistics, and Univariate and Bivariate LISA methods explore inequalities, concentration, and clustering patterns of rich-poor households at the district level. Additionally, spatial regression models such as OLS, GWR, and MGWR help to uncover spatial disparities and variability. Our findings demonstrate significant regional disparities, with the affluent household concentration being notably higher in north-western and southern India, while central, eastern, and northeastern regions exhibit greater inequality. Key factors impacting wealth inequality include rurality, low female literacy rates, educational level of household heads and prevalence of Scheduled Castes/Tribes. This study highlights the spatial dimensions of wealth inequality and provides a nuanced understanding of the factors contributing to these patterns. The GWR and MGWR models prove most effective, explaining more than 90% of the variation in wealth distribution factors. This study sheds light on the spatial dynamics and factors behind wealth disparities in India, offering strategic insights for equitable growth initiatives targeting diverse socio-economic sectors. • Widening wealth gap has far-reaching consequences for society. • Sharp Rich-Poor contrast: Northwest & south vs. central, eastern & northeastern India. • Education, rurality, female literacy are key factors influencing rich-poor divide. • Bi-LISA reveals localized clustering pattern for both Rich vs. Poor. • GWR, MGWR models explain over 90% of wealth distribution variation effectively. [ABSTRACT FROM AUTHOR]

The socio-economic literature has focused much on how overall inequality in income distribution (frequently measured by the Gini coefficient) undermines the "trickle down" effect. In other words, the higher the inequality in the income distribution, the lower is the growth elasticity of poverty. However, with the publication of Piketty's magnum opus (2014), and a subsequent study by Chancel and Piketty (2017) of evolution of income inequality in India since 1922, the focus has shifted to the income disparity between the richest 1% (or 0.01%) and the bottom 50%. Their central argument is that the rapid growth of income at the top end of millionaires and billionaires is a by-product of growth. The present study extends this argument by linking it to poverty indices in India. Based on the India Human Development Survey 2005–12 – a nationwide panel survey-we examine the links between poverty and income inequality, especially in the upper tail relative to the bottom 50%, state affluence (measured in per capita income) and their interaction or their joint effect. Another feature of our research is that we analyse their effects on the FGT class of poverty indices. The results are similar in as much as direction of association is concerned but the elasticities vary with the poverty index. The growth elasticities are negative and significant for all poverty indices. In all three cases, the disparity between the income share of the top 1% and share of the bottom 50% is associated with greater poverty. These elasticities are much higher than the (absolute) income elasticities except in the case of the poverty gap. The largest increase occurs in the poverty gap squared – a 1% greater income disparity is associated with a 1.24% higher value of this index. Thus the consequences of even a small increase in the income disparity are alarming for the poorest. [ABSTRACT FROM AUTHOR]

Having suffered for over 18 months from COVID-19, the Indian economy appears to be on recovery path now. However, despite recovery in some sectors, the economy presently suffers from numerous challenges. The first big challenge confronting our economy is related to poverty and hunger. The second problem is related to inequalities. The paper points out that if a country attempts to achieve high growth rate on the global level, the rich will become richer while the poor will become poorer. The paper also describes multi-dimensional poverty, which is extremely high in Bihar, Jharkhand, U.P. and M.P. A big challenge confronting Indian economy is the rising burden of debt. Another challenge which our economy is facing is 'corruption'. A very formidable challenge which faces Indian economy is related to urban rural divide. The paper describes various facets of the gap between cities and villages and highlights that the switch over from planned development to adhocism is not appropriate for India. [ABSTRACT FROM AUTHOR]

In the Indian economic scenario, the primary sector or agriculture-related sector is the major source of national income, and it shares around 18% of India's GDP. Although around 40 percent workforce of the country is employed in this sector, the productivity is relatively at a low level. The unequal and staggered distribution of land leads to the low productivity in agriculture. Inequality in the land distribution is defined as the differences in the size of land holdings possessed by various individuals or households. It is known that the size of landholdings varies from household to household. The widely used measure of inequality i.e. Gini's coefficient has been applied in this study by using NFHS India datasets. In this study, it is observed that the proportion of landless population has increased continuously in the country especially in the states where major population has involved intensely in the agricultural works. [ABSTRACT FROM AUTHOR]

Due to unavailability of consistent income data at the sub-state or district level in developing countries, it is difficult to generate consistent and reliable economic inequality estimates at the disaggregated level. To address this issue, this paper employs the association between night time lights and economic activities for India at the sub-state or district-level, and calculates regional income inequality using Gini coefficients. Additionally, we estimate the relationship between night time lights and socio-economic development for regions in India. We employ a newly available data on regional socio-economic development (Social Progress Index), as well as an index that represents institutional quality or governance. Robust to the choice of socio-economic development indicators, our findings indicate that regional inequality measured by night time lights follow the Kuznets curve pattern. This implies that starting from low levels of socio-economic development or quality of institutions, inequality rises as regional socio-economic factors or quality of institutions improve, and with subsequent progress in socio-economic factors or quality of institutions, regional inequality declines. [ABSTRACT FROM AUTHOR]

Rationale: A great wealth of studies expound on the impact of water and sanitation facilities on sustainable human development. But even though water-sanitation nexus is acknowledged in WaSH (Water-Sanitation-Hygiene) literature, they are seldom assessed collectively. In rural India, open defecation is still a major threat to human health, as much as potable water quality. Unfortunately, no study yet exists that attempts to assess the WaSH sector in a holistic sense. Objective: Present study was aimed to integrate multiple WaSH parameters into a composite WaSH Quality Index (WaSHQI) for rural India, within a geospatial framework, and understand potential effects of different sociodemographic factors that are likely to influece WaSH profile development. Methods: District-wise data for (i) within-premises latrine facility, (ii) water source type (safe/treated tap), (iii) water source location (near home/away from home), and (iv) wastewater drainage (closed/open) were mapped at nationwide scale. Gini Coefficients were computed for each parameter to elucidate spatial inequality. The parameters were integrated in various combinations to compute a composite index for each district called, WaSHQI. In the process, four hypothetical scenarios were generated (grading from most conservative to most liberal). The WaSHQI was later (a) merged with spatial algorithms (Moran's I and LISA)) to identify WaSH-hotspots and (b) correlated with a range of sociodemographic factors (e.g., literacy, household density, caste). Results: Under a conservative aproach (presumably the most hygienic WaSH scenario), a vast expanse through central India were significantly (p < 0.001) lagging in multiple WaSH facilities and appeared as major hotspots that deserve urgent management actions. On the other hand, northwestern states (Punjab and Haryana) registered a better WaSH profile owing to a number of progressive social reforms. Significant (p < 0.01) correlations between the WaSHQI and literacy levels, especially that of female, in the hotspots called for more in-depth region-specific investigations in future. Rural WaSH sector in India is marked by intense spatial inequality/heterogeneity, calling for spatially-optimized interventions. Using multiple geospatial alrorithms and statistical analyses the study demonstrated the spatially interconnected nature of the WaSH and argued that policy decisions have to address the parameters collectively. Future [ABSTRACT FROM AUTHOR]

The global rise of life expectancy at birth has attracted worldwide interest, especially in understanding the pace of mortality transition in developing countries. In this study, we assess the progress of mortality transition in India during four decades between 1970 and 2013. We estimate measures of mortality compression and variability in age at death to assess the trends and patterns in mortality compression for India as a whole and its twelve biggest states. The results reveal an unequivocal convergence pattern in mortality compression across the states underpinned by the reduction in premature mortality and emerging homogeneity in mortality. Results by gender show that women are more homogenous in their mortality across the country because of an explicit reduction in the Gini coeffi cients at age 10 by the age group of 15-29 years. Mortality compression has changed in recent decades because of the increased survival of women in their reproductive ages, which marked a distinct phase of mortality transition in India. The pace of mortality transition, however, varies; adult mortality decline was greater than senescent mortality decline. These results show that India has passed the middle stage of mortality transition and has entered an early phase of low mortality. [ABSTRACT FROM AUTHOR]

This paper is a contribution to understanding income generation and inequality in India's agricultural sector. We analyze the National Sample Surveys of agriculture in 2003 and 2013 using descriptive and regression based methods, and estimate income inequality in the agricultural sector at the scale of the nation and its 17 largest states. We show that: (a) there are significant state‐level differences in the structures/patterns of income generation from agriculture, (b) there is a negative relationship between the amount of land owned by the household and share of wages in total income, (c) income inequality in India's agricultural sector is very high (Gini Coefficient of around 0.6 during the period), and (d) about half of the income inequality is explained by the household‐level variance in income from cultivation, which in turn is primarily dependent on variance in landownership. [ABSTRACT FROM AUTHOR]

• The accuracy of methods to calculate the global distribution of income has not yet been tested. • Among four methods, the Lorenz-curve regression method is the most accurate. The two-parameter distribution method is also very precise. • On the basis of our new dataset, we find that income inequality among the citizens of 145 countries declined significantly between 1988 and 2015. • Our new method to deconstruct the change in the global Gini coefficient of income inequality reveals that income convergence was the main driver. • Without China and India, global interpersonal income inequality in 143 countries was higher in 2015 than in 1988. While various methodologies have been used in the literature to estimate global interpersonal income inequality, the accuracy of these methods has not so far been tested. We compare the accuracy of four methods and find that the Lorenz curve regression method is the most accurate and robust, while the accuracy of the identical quantile income and the Kernel density methods depends on the level of detail about income shares. The simple two-parameter distribution method is also very accurate when either the Log-normal or the Weibull distribution is used. Using the two-parameter distribution method, we show that global income inequality among the citizens of 145 countries declined significantly between 1988 and 2015, largely because of the convergence of income per capita, which was offset to a small degree by the increase in within-country inequalities and the increased population share of poorer and more unequal countries. Regional income inequality declined in most parts of the world, with the notable exception of developing Asia where it has increased. Despite the large increases in within-China and within-India inequality, income convergence of the two countries drove down global income inequality. Without China and India, global interpersonal income inequality in 143 countries was higher in 2015 than in 1988, indicating that more than half of the world has not really become more equal. [ABSTRACT FROM AUTHOR]

The article attempts to provide empirical evidence on the relationship between human capital and income inequality in India in a non-linear and asymmetric framework. To capture both long-run and short-run asymmetries, we have employed the non-linear autoregressive distributed lag approach using the relevant data from 1970 to 2016. Findings of the article suggest that education expansion acts as a major factor in reducing prevailing high income inequality, that is an increase in average years of schooling results in more equal distribution of income. In contrast, high economic growth, inflation and trade openness create unequal distribution of income. The asymmetric causality test results indicate that there is unidirectional causality running from female human capital, economic growth and inflation to income inequality. From a policy perspective, we suggest that education expansion should be used as a powerful tool to mitigate income inequality by emphasizing the quality of education. At the same time, policies geared towards social benefits, inclusive education, training for unskilled workers and price stability should be encouraged to attain fair income distribution in India. [ABSTRACT FROM AUTHOR]

Purpose: Though Indian economy since 1980s has expanded very rapidly, yet the benefits of growth remain very unequally distributed. The purpose of this paper is to provide new evidence about the shape, intensity and decomposition of inequality change between 2005 and 2012. The authors find that Gini, as a measure of income inequality, has increased irrespective of geographic regions. Design/methodology/approach: Based on a recent distribution analysis tool, "ABG," the paper focuses on local inequality, and summarizes the shape of inequality in terms of three inequality parameters (α, β and γ) to examine how the income distributions have changed over time. Here, the central coefficient (α) measures inequality at the median level, with adjustment parameters at the top (β) and bottom (γ). Findings: The results reveal that at the middle of distribution (α), there is almost the same inequality in both the periods, but the coefficients on the curvature parameters β and γ show that there is increasing inequality in the subsequent period. Finally, an analysis of decomposition of inequality change suggests that though income growth was progressive, however, this equalizing effect was more than offset by the disequalizing effect of income reranking. Research limitations/implications: This paper shows how it can be possible both for "the poor" to fare badly relatively to "the rich" and for income growth to be pro-poor. Practical implications: This paper stresses the significance of inequality reduction. Social implications: Inequality reduction is very much imperative in ending poverty and boosting shared prosperity. Originality/value: Perhaps, this research work is first of its kind to examine the shape and decomposition of change in income inequality in India in recent years. [ABSTRACT FROM AUTHOR]

The paper aims to analyses the relationship between educational expansion and schooling inequality in India across states and over the age cohort. The focus of the paper is to verify the inverted-U shaped relationship between the mean and dispersion of schooling. The evidence of an inverted-U shaped relationship between the mean and dispersion of schooling is found when dispersion is measured in terms of standard deviation which indicates that as the average level of schooling increases, educational inequality first increases, and, after reaching a peak, starts declining in latter phases of educational expansion. The turning point occurs when average year of schooling is about 7 years. The same inverted-U shaped relation is not observed when inequality in schooling is measured in terms of Gini-coefficient. [ABSTRACT FROM AUTHOR]

The focus of the paper is to analyze the position of personal loans disbursed by the scheduled commercial banks in India for the period of 2004-05 to 2015-16 (latest data available from the RBI report on personal loan details). RBI data show that the maximum share of total personal loan goes mostly to the Southern region which is distantly followed by the Western region and a very small percentage remains for the North-Eastern region. With regard to the regional concentration of the personal loan portfolio of banks, the Herfindahl-Hirschman index (HHI) value lies in the range of 2379 to 2604. In terms of inequality in distribution across the regions, disparity is quite high with Gini coefficient value ranging between 35 and 40 during the period. In terms of growth rate of personal loan per capita, the Southern and Western regions come at number two and three respectively. The growth in this loan category in the North-East is surprisingly more than the other states and this is mainly due to the sudden rise in flow of this loan during the past few years. With regard to the inter-regional difference, the statistical tests show a significant difference among the regions. [ABSTRACT FROM AUTHOR]

Provision of drinking water is considered to be an essential public service. Ensuring adequate water supply remains a challenge in Indian cities that are experiencing rapid growth and often exhibit a mismatch between increasing demands and inadequate supply infrastructure. This study quantifies the existing inequality in water supply within Indian cities through Lorenz curve, Gini coefficient as well as Theil indices. Two types of Theil indices are estimated to gain different perspectives: water supply and population-weighted. Both the Theil indices are disaggregated, according to economic and regional categorisation of the cities, to explore the within- and between-group inequality. The water supply and population-weighted Theil indices provide different outlook of the inequality amongst the cities. But the population-weighted index is often better and pragmatic. Further, the inequality in access to tap water in India is studied by estimating modified Lorenz curves and Theil indices. Again, the Theil indices are decomposed into within and between components according to economic and regional grouping of states. The results suggest that there is disparity in supply of water in India, and infrastructure has to be boosted to meet the growing demand. This study is a step towards quantification of water supply inequality. The approach used in the study can contribute to monitoring of water supply equity as well as in formulating sustainable and equitable water policies. [ABSTRACT FROM AUTHOR]

The institution of tenancy has the capacity to reduce rural inequality by more equitable distribution of operational holding than that of ownership holding. This paper attempts to examine the distributive implications of tenancy on the landholding pattern of farming households across Indian states, with specific focus on West Bengal. The study is based on both secondary and primary sources of data. The secondary source of information on distribution of ownership and operational holdings is exclusively based on decennial land household surveys (from 1970-71 to 2012-13) by NSSO. Due to a certain underestimation of the extent of landlessness and the extent of tenancy and inequality in ownership and operational holdings in the NSS data, a renewed attempt has also been made in this paper to shed some light on the micro-empirical aspects of the distribution of landholdings and leasing behaviour of households in the district of Burdwan, West Bengal. Empirical evidence suggests that the institution of tenancy acts as a redistributive mechanism to reduce rural inequality by making the distribution of operational holding more egalitarian than the ownership distribution. It is expected that the institutional intervention by transferring property rights would create a conducive environment for ensuring inclusive rural development. [ABSTRACT FROM AUTHOR]

The mismatch between trade-embodied economic benefits and CO 2 emissions causes carbon inequality, which is seldom analyzed from the intracountry level, especially across a long-term period. This study applied an environmentally extended multiregional input-output model to trace this mismatch and measure the carbon inequality quantitatively within China during 2007-2017. The results show that during the past decade, China's national carbon inequality was continuously worsening with carbon Gini coefficients rising regardless of production- (0.21-0.30) or consumption-based (0.12-0.18) accounting. The regional carbon inequality was deteriorating, where less developed provinces with 20% of total value-added emitted 32.9% of total CO 2 emissions in 2007, while this figure rose to 42.6% in 2017. The eastern provinces (Jiangsu and Shanghai) had entered into net economic and carbon beneficiaries keeping high trade advantages, by contrast the northwest provinces (Ningxia and Xinjiang) were trapped in a lose-lose situation with trade benefits declining by 68%. The southwest provinces (Yunnan and Guangxi) shifted from being net carbon and value-added exporters to net importers, stepping into the earlier development mode of eastern provinces. This hidden and exacerbated carbon inequality calls for regional-specific measures to avoid the dilemma of economic development and CO 2 mitigation, which also gives a good reminder for the rising economies, like India.

One issue that has attracted considerable attention recently among scholars interested in inequality and conflict is polarization. We analyze polarization in India over roughly the past three decades using consumption expenditure data. We show that both bipolarization and multidimensional polarization (on several dimensions: rural–urban, state, region) have increased since the 1990s. In the case of bipolarization, this is a reversal from an earlier trend (in the 1980s). Overall, our results suggest that the high growth that India has witnessed since the 1990s has been associated with widening disparities. Comparing polarization and inequality trends, we find similarities, but also some differences; we also show how the study of polarization can provide different insights. Our results therefore underscore the importance of studying polarization as distinct from traditional inequality. [ABSTRACT FROM PUBLISHER]

Using the newly collected data from 575 household coffee farmers in the traditional coffee-growing regions of India, this paper measures inequality in size distribution of coffee estates. Inequality is linked to poverty by modelling the determinants of probability of abject poverty of farmers with reference to inequality measures, social caste, human capital endowments, income from coffee cultivations and types and varieties of coffee grown. Empirical results show remarkable variations in levels of inequality across regions and social groups. Binary Logit estimates show that inequality elasticity of poverty is positive and biggest. Other significant determinants of poverty imply that farmers who belong to socially disadvantaged groups, who are lower educated, who have lesser gross returns, who grow mono-type coffee or cultivate Selection.9 and Selection.6 varieties are more vulnerable to poverty. These new and crop-specific results have implications for redistributive-oriented and inclusive promotional policies for household coffee farmers in India and applicable for other coffee-growing developing countries in Asia. [ABSTRACT FROM AUTHOR]

Studies of undernutrition in India (and elsewhere) have focused exclusively on interpersonal inequalities, and estimates of the magnitude of inter-group inequalities are unavailable. A focus on “horizontal”, or group-based, inequalities offers vital policy insights that would be lost in an approach based purely on interpersonal inequalities. We therefore apply the group analogues of Atkinson's index and the Gini coefficient to shed light on the disproportionate burden of undernourishment borne by rural and historically vulnerable caste groups. Furthermore, the prominent determinants of inter-group disparities are identified through Blinder–Oaxaca decomposition analysis. The paper calls for explicit targeting of backward castes across the country and improved inter-sectoral collaboration to ensure equitable access to education, health care and water and sanitation, particularly across underdeveloped regions. [ABSTRACT FROM AUTHOR]

The present paper attempts to explore the pattern of industrial growth in India since 1980. Both the descriptive and panel regression analysis are done for estimating the results. To ascertain the impact of the 1991 economic reforms in determining the structure of industrial growth, comparative analyses of the pre- (1980–81 to 1991–92) and post-reform periods (1992–93 to 2005–06) were also done. The overall results show that the Indian manufacturing industries are dominated by the capital-intensive low technology industries. This indicates that in the industrial sector, the higher proportion of low technology industries prevails. Further, using the Gini coefficients, the actual pattern of Indian industrial growth is determined. The study also failed to find a direct relationship between economic reforms and structural transformations within the sector. Moreover, the historical and empirical evidence points towards the investment in indigenous R&D as an important factor in determining growth and sustainability. But, for the process of technological accumulation, the role of government seems important. [ABSTRACT FROM AUTHOR]

The article focuses on the cross-state variations in India as an important economic issue. The fundamental relationships between income inequality and economic growth in Indian states is examined in a time-series study of figures for the period 1980 to 2009-2010, including relevant macroeconomic indicators. Rusults show the significant impacts of human capital investment, Gini coefficients, and macroeconomic volatility on the divergent growth trends.

Abstract: This work presents a comprehensive study of the evolution of the expenditure distribution in India. The consumption process is theoretically modeled based on certain physical assumptions. The proposed statistical model for the expenditure distribution may follow either a double Pareto distribution or a mixture of log-normal and Pareto distribution. The goodness-of-fit tests with the Indian data, collected from the National Sample Survey Organisation Reports for the years of 1983–2007, validate the proposal of a mixture of log-normal and Pareto distribution. The relative weight of the Pareto tail has a remarkable magnitude of approximately 10%–20% of the population. Moreover, though the Pareto tail is widening over time for the rural sector only, there is no significant change in the overall inequality measurement across the entire period of study. [ABSTRACT FROM AUTHOR]

This article reports on mean consumption, poverty (all three FGT measures) and inequality during 2004 for rural India using National Sample Survey (NSS) data for the 60th Round. Mean consumption at the national level is much higher than the poverty line. However, the Gini coefficient is higher than in recent earlier rounds. The headcount ratio is 22.9 per cent. Mean consumption, all three measures of poverty and the Gini coefficient are computed at the level of 20 states and 63 agro-climatic zones in these 20 states. It is surmised that despite impressive growth rates deprivation is pervasive, pockets of severe poverty persist, and inequality is rampant. [ABSTRACT FROM PUBLISHER]

Abstract: Energy planning exercises for rural areas make use of a mix of locally available renewable resources with some commercial resources to cater to the energy needs of the population. Such exercises are economically attractive in developing countries, whereby, the foreign exchange reserves for the purchase of commercial energy is curtailed. The first step in the implementation of an energy planning exercise is to understand the energy consumption and utilization habits of the population being served. Frequently, an assessment of the levels of inequality in the consumption of various resources is necessary as, this provides the rural planner with an understanding of the future trends and thus forearms him with strategic alternatives to combat any future energy resource crisis that the trends seem to imply. In the present paper, an attempt is made to assess the level of energy resource consumption inequality in a typical hilly rural Indian village. The Gini Coefficient of Inequality, a measure of inequality in the field of Econometrics has been applied for this assessment. The population is segregated into different categories based on their income levels and certain socio-economic criteria, which are also felt to exercise an influence on consumption levels of energy. The results of the analysis are then discussed in the light of the findings. [Copyright &y& Elsevier]

This article examines the structural aspects of climate vulnerabilities in the context of monsoon failures. The paper is based on a unique household survey, conducted in Tamil Nadu, India. The study uses a rural differentiation framework to interrogate unequal vulnerabilities to monsoon failures, based on measures such as Gini coefficients and Lorenz curves of monetary losses. Results show that negative consequences of climate change in general, and monsoon failures in particular, intensify pre-existing socio-economic disparities. When the rural differentiation theory is applied in a broader sense, the analysis shows that landed and farming households have greater exposure and losses. When we move beyond these aggregate categories, the revelation is that households with pre-existing disadvantages such as marginal landholders, subsistence farmers and agricultural workers are more vulnerable. • Global warming affects agriculture in South Asia in a major way through monsoon failures. • Vulnerability to monsoon failures can be measured by associated monetary losses. • These losses are highly unevenly distributed, pointing to significant inequality in impacts. • Landless households, marginal holders and subsistence farmers have higher losses. • Climate change intensifies existing structural disadvantages. [ABSTRACT FROM AUTHOR]