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Using annual time series data for India, this research paper examines the presence of asymmetric cointegration and asymmetric causality between financial development and poverty reduction using nonlinear autoregressive distributed lag (NARDL) model and asymmetric causality test. The empirical findings support the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The result emanating from asymmetric causality test reveal a unidirectional asymmetric causality between negative shocks in financial development and poverty. Moreover, expansionary policies of financial development are found to serve as catalysts to spur poverty alleviation while contractionary policies of financial sector are found to exacerbate poverty in an asymmetric and nonlinear fashion. The findings of Wald's test also confirm the presence of asymmetric effects in the poverty-finance nexus. The asymmetric cumulative dynamic multipliers used to examine the behaviour of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator and therefore demonstrate their robustness. The present study divulges the need for investigating asymmetry in finance-poverty nexus in order to draw policy-relevant conclusions. The authors conclude that financial development serves as a panacea and antidote to the scourge of extreme poverty in India. We recommend regulation of informal sources of credit, financial inclusion of poor, credit boost to small and medium enterprises employing rural poor and channelization of credit to productive sectors with high employment elasticity to be persistently encouraged for poverty alleviation in India. [ABSTRACT FROM AUTHOR]

To meet the national development goals in India on poverty alleviation and to trail the Sustainable Development Goals (SDG), policy makers need to have adequate information on poverty in the country. To this end the aim of this paper is to analyse the trends in multidimensional poverty at the all-India level, across geographic locations, castes and religious groups. We have used Alkire–Foster methodology to measure multidimensional poverty index (MPI) and utilized National Family Health Survey unit level data of the latest three rounds 2005–06, 2015–16 and 2019–21. To the best of our understanding this is the first paper that utilizes the latest data sets to analyse the trends of MPI in India. We have also made a comparative assessment of trends of poverty in India measured by Global MPI approach and India's MPI approach. Over the period 2005–2006 to 2019–2021 the absolute decline in MPI was larger in rural areas of India. However, the contribution to MPI in rural areas is relatively high and that increased over time. There was no evidence of reduction of inter-caste and inter-religious based disparities. There are larger doses of decline in MPI in the sub period 2015–2016 to 2019–2021 but the decline across the states of India continues to be non-regressive. The states which were worst performing in 2005–2006 continue to be the same in 2019–2021. The paper concludes that by exploring the MPI over time one can decipher the urgencies in policy development to move towards the SDGs. [ABSTRACT FROM AUTHOR]

There is a debate surrounding the nexus between poverty and environmental degradation. While the predominant school of thought argues that poverty is directly responsible for environmental degradation, another school of thought argues that poor do not have the resources which would force them cause environmental degradation. Empirical support for both the arguments, however, is based mostly on macro data. Using micro level data, this paper makes an attempt to examine whether poverty is a factor determining forest degradation in the state of Odisha in India. The study is carried out in two districts, divergent from each other in incidence of poverty, forest coverage and percentage of Scheduled Tribe population. The study finds no empirical evidence that poverty affects degradation of forest. On the other hand, there is evidence of forest degradation with the increase in income, though region specific. Hence, it is non-poor households than poor one who could be responsible for forest degradation. This result therefore does not support the downward spiral hypothesis and questions the assumption that poverty alleviation is an essential part of avoiding forest degradation. However, importance of poverty reduction cannot be overlooked, and effective forest management can be a way to address poverty. [ABSTRACT FROM AUTHOR]

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

This study investigates the level and predictors of life satisfaction in people living in slums in Kolkata, India. Participants of six slum settlements (n = 164; 91% female) were interviewed and data on age, gender, poverty indicators and life satisfaction were collected. The results showed that the level of global life satisfaction in this sample of slum residents did not significantly differ from that of a representative sample of another large Indian city. In terms of life-domain satisfaction, the slum residents were most satisfied with their social relationships and least satisfied with their financial situation. Global life satisfaction was predicted by age, income and non-monetary poverty indicators (deprivation in terms of health, education and living standards) (R2 15.4%). The current study supports previous findings showing that people living in slums tend to report higher levels of life satisfaction than one might expect given the deprivation of objective circumstances of their lives. Furthermore, the results suggest that factors other than objective poverty make life more, or less, satisfying. The findings are discussed in terms of theory about psychological adaptation to poverty. [ABSTRACT FROM AUTHOR]

The study utilized the tree covers per cent, agroforestry suitability, present and future (2050) climate, agriculture vulnerability (2050), percentage of people living Below Poverty Line (BPL) data sets and manoeuvered them in GIS platform to understand the agroforestry extent, potentiality and the critical multidimensional relationship among them. The total agroforestry area in India (if defined the tree cover per cent greater than 10% on agricultural land) was found to be 28 million hectares that is approximately 17% of the total agriculture land area which is remarkably less (global average 43%). The analysis further revealed that the agriculture land potential in India towards the agroforestry suitability category (S1: High suitability) is alone 75.6 million hectares that are 2.7 times of total existing agroforestry extent. Among all agro-ecological regions of India, the Eastern Plain agro-ecological region has high cropland potentiality which will help significantly in magnifying agroforestry set-up in the future. The analysis further revealed a very high poverty per cent (41–80%) category has approximately 5.3 million hectares of land under agroforestry, whereas the cropland potentiality (category S1) towards agroforestry was found approximately four times of the present agroforestry extent. The Western Ghats and the Coastal Plain agro-ecological region maintain a diversified agroforestry environment that will face double risk in the future (2050) due to precipitation deficit and also from significant temperature increase. Our analysis highlights the important agroforestry-related findings that will assist crucially to the decision-makers of India for implementing synergic strategies/planning of agroforestry at country/state/district/village levels. [ABSTRACT FROM AUTHOR]