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Mainstream, VOL 61 No 40 September 30, 2023

In Need of Immediate Actions: Tracing the New Poor and their Vulnerability | Chattopadhyay & Pratim Sahu

Saturday 30 September 2023

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The COVID-19 pandemic has presented itself as an unprecedented ‘crisis of livelihood’. Poor people, due to their nature of jobs and limited economic resilience, have received the maximum jolts. As per the IMF study (2021) [1], COVID-19 has pushed 97 million more people into poverty.

Ironically, the vulnerability of rural livelihoods is greater consequent upon any economic shocks, let alone the pandemic. This is attributed to a combination of factors operating at the household levels - heavy dependence on traditional input and output supply chains; high engagement in informal wage and non-farm employment; and pre-existence of high level of poverty and food insecurity. Moreover, lockdown-related trade and mobility restrictions and disruptions in economic activities provide distinct character to the livelihood crisis.

Contours of livelihood crisis

In India, rural areas were already reeling with agrarian distress, disappearance of livelihood avenues, declining female labour force participation rates, rising youth and educated unemployment rates. A compressive study by UNICEF (2021) [2] on the impact of COVID 19 on the vulnerable population in India revealed increased casualization of work, higher availability of poorer quality works and significant as well as persistent decline in wages in the post-COVID period. Even the benefits of job creation under the MGNREGS were subdued by delays in wage payments.

Problems of pre-COVID-19 food insecurity has also further worsened. Fewer employment opportunities coupled with lockdown-induced supply chain disruptions had adverse impacts on income and food prices. Apart from insufficient access to food, the households suffered in term of quality of the food consumed and future availability of food. Increased expenditures on health and hygiene products resulted in lower expenditures on essential food items along with curtailment of consumptions of protein-rich food items. Intra-household inequity in access to food was also pronounced as women were often forced to sacrifice their foods. All these are likely to severely undermine the child growth and nutrition of the unborn child in the households.

Grounding the coping strategies and policy responses

Reduced consumption of goods, use of savings and borrowing for covering living expenses, sale of productive assets including farming equipment and livestock and reduced productive investment on health and education services were some of the coping strategies adopted by households across rural India. In fact, the near absence of formal risk-management procedures has forced the rural households to rely heavily on such adverse coping strategies. Government initiatives have largely turned out to be ineffective in providing adequate income and employment-generating opportunities in the post-pandemic periods. These are expected to have lasting effects on household livelihoods and could trap them into low equilibrium poverty with little opportunities for escape. Gram panchayats in India, leveraging it’s better knowledge of local priorities and legitimacy as institutions of local government, played a critical role in identifying the poor people in need of social support as well as the nature of support they required. The effectiveness of pandemic responses in Kerala is largely attributed to the presence of empowered gram panchayats enjoying a trust and collaboration between citizens and local officials.

Imperatives for profiling the ‘new poor’

In the post-COVID era rural India may observe both the further deterioration of existing poor and creation of new poor. The ‘new poor’ represents a novel socio-economic group with motivations and aspirations that are dissimilar with that of the existing poor. It is imperative to identify and profile new poor, i.e. to understand who they are, where they live and work, and how they have been affected by the crisis?

Covid induced loss of learning and loss of skill have engendered a distinct learning poverty among both existing poor and non-poor at the margin. The latter groups are more likely to slip into new poor club and subsequently, both the groups will continue to stay poor for a longer duration. In particular, the students would experience longer and constrained ‘school-to-work’ transition with adverse impacts on their employability. Similarly, workers witnessing skill loss would find it difficult to get into the labour market.

A large part of existing research is, however, on the stock of poverty and its correlates and the issues of flows into and out of poverty have not been adequately understood in India. Therefore, many of the government schemes are designed to help people escape poverty and not prevent people from descending into it. But in reality, one single event or shock (i.e. indebtedness, chronic illness, marriage, and crop failure) can descend a family into the poverty zone. One of the seminal works titled ‘One illness away: Why people become poor and how they escape poverty’ by Anirudh Krishna (OUP, 2010) [3] highlighted the need for public policy to focus also on preventing people from falling into poverty.

In recent times, the government has abruptly withheld the 2017-18 consumption survey and also postponed the Census 2021 more than once. Even the Socio Economic Caste Census is too backdated to understand the changing contours of poverty dynamics. In fact, such a long gap in collection and publication of these important data are unusual in India with a rich history of robust statistical system. Thus, along with a strong plea to bring out such data, it is essential to undertake evidence-based research on poverty flows by identifying households who escaped poverty (or who fell into poverty) and comparing the experiences of such households with those of others who remained poor (or who stayed out of poverty). The whole range of enabling (and disabling) factors must be analysed to understand: a) what needs to be done for improving households’ chances for escaping poverty, b) what should be done for lowering the risks of descent; and c) how should both preventive and supportive policies be designed in the wake of pandemic?

Leveraging the local governments

The COVID-19 has also necessitated rethinking of role of the local governments. Regular poverty tracking (high-frequency monitoring surveys) may be introduced as a non-negotiable (routine) activity of Gram Panchayat. A Modified Participatory Identification of Poor (MPIP) may be designed with a new set of indicators to understand and capture the impacts of pandemic on rural households. The existing cadre of Community Resource Persons (CRPs), if capacitated and trained, can play a crucial role in identifying new poor families. The Gram Panchayat Development Plan (GPDP) can play a direct role in profiling and mapping the needs of the new poor as well as prioritising resource allocations for the new poor. Kerala, with strong support from local institutions, has started preparing micro plans for identifying extreme poor families and design an immediate care plan, intermediate plan and long-term comprehensive plan to bring transformative changes in their lives and livelihood. Such micro-planning needs accurate data. Collection and management of local data on rapidly changing dynamics of poverty need to be prioritized. This data are also to be shared with panchayat level line departments that should work in close coordination with the gram panchayats. Indeed, convergence will be the key to envisage a poverty-free panchayat and to mainstream new poor (and existing poor) in the overall rural development strategies and economic policies.

(Authors: Soumyadip Chattopadhyay, Associate Professor, Department of Economics and Politics, Visva-Bharati University Email: soumyadip.chattopadhyay[at]gmail.com ; Partha Pratim Sahu, Associate Professor, Centre for Good Governance and Policy Analysis (CGGPA), National Institute of Rural Development and Panchayati Raj (NIRDPR) E-mail: ppsahu.nird[at]gov.in )

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