The Migrant Economy During the Pandemic: An Exploratory Study in Baisi Block, Bihar

One of independent India’s successes, improving life expectancy at birth from about 30 years in the 1950s to the 70s in the 2000s, has also exposed a

Policy making, to be effective, requires assessments of magnitudes and trends of major events based on evidence. One of the objectives of government policy interventions is—or should be—to pick up and stem slides in standards of living when they occur. For a stubbornly poverty-stricken country such as India, this function of the state assumes even greater significance when calamities, such as the COVID-19 pandemic, descend on the populace. Although the Government of India is yet to release data on the population pushed into poverty as a result of the pandemic, research organisations—both national and international—have attempted to study this important link. These studies throw light on the important issue of arriving at estimates of the numbers of people that might have been pushed into poverty as a consequence of COVID-19, and therefore on the magnitude of the problem confronting any conscientious policy-maker. The first of the two estimates assessed in this essay is due to researchers at the Pew Research Centre (PRC) in the U.S., and the second to researchers at the Centre for Sustainable Employment at Azim Premji University (APU) in India. In this Issue Brief, S. Subramanian, Economist, and author of Inequality and Poverty: A Short Critical Introduction, and other books on poverty, seeks to reconstruct the assumptions and data inputs that have gone into the making of the estimates under review. Analysing the estimates, which suggest vastly differing outcomes, he discusses the manner in which poverty figures are arrived at to provide a quantitative picture of economic deprivation. In the immediate context, and on the basis of such data as are available, he concludes that it could be reasonably estimated, in line with the APU study, that anywhere upward of 200 million people may have slid into poverty after the first wave of the COVID-19 pandemic. This finding assumes importance as an aspect of evidence-based assessment of the economic devastation that has accompanied the pandemic. It points even more specifically to the role of the state, or its relative absence, in safeguarding its peoples from a once-in-a-century, long-drawn out catastrophe which has persisted for over a year. Behind these numbers are real people, whose predicament would have been better served by a state with a mind to basing policy intervention on evidence, not least when such research evidence is available in the public domain. Even based on a partial assessment, the two main pandemic responses by the government – a hastily declared lockdown and reluctantly ad-hoc relief measures – have resulted in “grievously harsh” consequences for India and its fight against poverty. By highlighting the outcomes of two earlier significant research efforts, Subramanian invites attention to importantly required numbers that would enable policy makers to get a sense of the enormity of the deprivation that has been caused by the COVID-19 pandemic. CONTENTS I. INTRODUCTION II. THE PRC ESTIMATE III. THE APU ESTIMATE IV. DIFFERENCES BETWEEN THE PRC AND APU ESTIMATES V. CONCLUDING NOTE I. INTRODUCTION This will be, for the most part, a data-and-methodology-related essay concerned with a seemingly antiseptic assessment of the possible impact of the first wave of the coronavirus pandemic on the magnitude of income-poverty in India. The concern is not only with a pandemic of historic magnitude, but also of a policy orientation that may have resulted in anywhere upwards of 200 million Indians sliding into poverty as a result of COVID-19 and the response to it.The focus of this essay will be on numbers and counting, and on the assumptions underlying these in an environment of scanty data accessed from different sources. In order to tell a narrative involving numbers, one can either focus on the manner in which they are derived, or shine the spotlight on the story that lies behind, and is reflected by, the data. In the present essay, the relative weight of emphasis is laid on the first of these two orientations, just so that the restricted focus of the exercise is preserved in the manner of its treatment. I shall confine commentary to a few observations, and not least because the numbers leave little room for any elaborately articulated opinion that is not immediately suggested by the quantitative evidence.In what follows, I shall try and spell out, as clearly as I am able to, the method by which the poverty numbers dealt with in this essay can be derived. These poverty numbers relate to the estimates that have been advanced in two earlier studies. 1.1 Different estimates of people pushed into poverty The first study is one by the Pew Research Center (PRC), Washington, D. C., USA (Kochhar, 2021), and the second is due to the Azim Premji University (APU), Bengaluru, India (APU, 2021). The two studies come up with vastly differing estimates of the additional numbers of people precipitated into poverty during the course of the first wave of the coronavirus pandemic in India. This, as might be expected, is on account of the differing data sets employed in the two studies. My effort is essentially to try and reconstruct these data sets, on the basis of the methodological guidelines available in the two respective studies. At one level, the effort may be justified simply in terms of the importance of keeping alive, in the public domain, the findings on pandemic and poverty revealed by the studies. They are of such vital contemporary significance that they must not be allowed to simply slip into forgetfulness or past history. Apart from this, there is a case for a painstaking—even plodding—expository exercise aimed at enabling laypersons and younger researchers to get a sense of the manner and method by which estimates of the sort discussed here are arrived at. In this justification, the focus is on the intrinsic utility of explanation, appraisal, and criticism. The two studies come up with vastly differing estimates of the additional numbers of people precipitated into poverty during first wave of the pandemic. My reconstruction does not yield results identical to the studies’ results, but the relevant sets of results are close enough to those in the originals. I should clarify, and reiterate, that the assumptions and input data sets I have attributed to the two studies are a product of my reconstruction of the methodological directions provided in the two studies, and any deviation there may be of my reconstruction from the actually employed methodology is certainly not due to wilful misattribution, but rather to obvious imperfections in my reconstruction. In particular, when I speak of the ‘Pew Research Centre’ and the ‘Azim Premji University’ data sets, I refer to my reconstructions of these data sets. Links to the studies by these organisations are provided under References. 1.2 Constructing poverty ratios With these preliminary clarificatory remarks out of the way, it is useful to begin by asking: what, typically, are the data one would need in order to estimate the headcount ratio of poverty (the proportion of the population that is poor)? It is useful to address this question because there are software computing packages available which can convert the requisite data into processed summary statistics of relevance to one’s interest. One such package is a readily accessible programme maintained by the World Bank, ‘POVCALNET’, which enables its user to feed in certain relevant data, which the programme processes. It then returns, by way of output, the headcount ratio of poverty (apart from a host of other related statistics on measures of central tendency and dispersion, such as the mean, the Gini coefficient of inequality, and a number of poverty indices). There are, typically, three items of data which the POVCALNET programme seeks, as enumerated and explained below 1 : The Income Distribution ( D ) . There are different ways in which income distribution data can be presented. A particularly convenient form is one which indicates the cumulative income share of each cumulated decile of the population, arranged from poorest to richest. That is, the data are presented in such a way that we have information on the income share of the poorest 10 per cent of the population, the income share of the poorest 20 per cent, the income share of the poorest 30 per cent,…, and so on, until we have accounted for all 100 per cent of the population. The income distribution is thus essentially depicted in a two-column table in which the first column lists the cumulated deciles of the population in ascending order of income and the second provides the cumulated income share corresponding to each cumulated population share. The Poverty Line (z) . The poverty line is a level of income such that all persons with incomes less than this level are considered to be poor . The Mean Income of the Distribution (m) . This is just the average income of the reference population. Once we feed these three inputs—namely D , z, and m —into the POVCALNET programme, it will tell us the associated headcount ratio of poverty for the given combination of income distribution, poverty line and mean income 2 . All of this is simple enough. The practical problem is to find the data on D and m , and to construct a reasonably convincing poverty line, z , which does the intended job of specifying a level of income that experience and judgement would endorse as an acceptable poverty line. These inputs are not readily available in the forms in, and for the time-periods for, which they would be required for constructing a picture of the impact of COVID-19 on the magnitude of poverty. Therefore, in order to assemble the needed information on the vital triad ( D , z , and m ) for any appropriate period (in this instance, the pre- and post-pandemic periods), a researcher would need to make certain assumptions and have resort to alternative sources of data.. Return to Contents II. THE PRC ESTIMATE As noted at the end of the introductory chapter, any assessment of changes in poverty on account of COVID-19 would depend crucially on our precise choice of the data inputs D , z, and m . At least one earlier effort at such an assessment for India (and indeed for other countries and the world as a whole) is due to the work of social scientists at the PRC, an institution which describes itself as a ‘non-partisan fact tank’, located in Washington, D.C., U.S. (see Kochhar, 2021) The Pew study estimates that an additional 75 million Indians may have been pushed into poverty after the first wave of the COVID-19 pandemic. The income distribution employed in this study is India’s 2011 consumer expenditure distribution, as available from the National Statistical Office (NSO), and the poverty line is taken to be the World Bank’s international poverty line of $2 at 2011 Purchasing Power Parity prices (converted to national currency and updated to take account of inflation). The ‘pre-COVID-19’ mean income is calculated on the basis of the World Bank’s (relatively optimistic) projection, made in January 2020, of the annual growth rate for 2019-2020. The ‘post-COVID-19’ mean is calculated on the basis of the World Bank’s (considerably depressed) estimate of this growth rate, made in January 2021. On the basis of these assumptions regarding D , z, and m , the Pew study estimates that an additional 75 million Indians may have been pushed into poverty after the first wave of the COVID-19 pandemic. The following three sub-sections present, in slightly greater detail, what I take to be the assumptions regarding the data inputs D , z, and m used in the PRC study. 2.1 The PRC Income Distribution Input As is well known, there are no systematic data available on the distribution of incomes in India. What we do have is information, from the quinquennial surveys conducted by the Central Statistical Organization’s (CSO’s) NSO, on the distribution of household consumption expenditure 3 . The latest official survey data pertain to the 68 Round of the NSO for the year 2011-12. It is these distributional data which seem to have been employed in the PRC analysis as a proxy for India’s 2020 income distribution. It should be mentioned that the 68 Round survey employs three ‘recall periods’, referred to, respectively, as the ‘uniform recall period’ (URP), the ‘mixed recall period’ (MRP), and the ‘modified mixed recall period’ (MMRP). Recall periods are important building blocks as they provide information on the expenses incurred by a household over specific time blocs, say a month or a year 4 . I take it that the distributional data employed in the PRC study correspond to the MRP estimates. The distributions are assumed to be the same for both the pre-COVID-19 and the post-COVID-19 periods. Table 1, which is derived from the National Sample Survey Organization’s 2011-12 data on rural and urban consumption distributions, summarises our data input on D . Table 1: Imputed Rural and Urban Income Distributions for 2020 Based on Corresponding Consumer Expenditure Distributions from National Sample Survey Data for 2011-12 (PRC) Table-1page-0002jpg Note: G stands for the Gini coefficient of inequality. Gini coefficients range from 0 to 1, representing perfect equality and inequality, respectively. Therefore, the higher the Gini coefficient, the greater the inequality. Source: Derived from data in Tables 1BR and 1BU of National Sample Survey (2014): Level and Pattern of Consumer Expenditure 2011-12 , NSS 68 Round, National Sample Survey Office, MoSPI, GoI, February 2014. It should be added that there are obvious caveats that must be issued about the use of consumption expenditure distributions as proxies for income distributions, which the PRC study acknowledges. For one thing, consumption distributions are typically less unequal than income distributions. For another, the same distributions are employed for both ‘pre-COVID-19’ and ‘post-COVID-19’ situations, which does not take into account the possibility that the impact of the pandemic on inequality might have been regressive. Thirdly, the consumption distribution data pertain to 2011-12, and the consumption distribution—especially in the urban areas of the country—has displayed a tendency to become more unequal over time. Having said this, there are situations in which—after a due observation of the attendant limitations of the exercise—one is constrained to employ the data that are available, in a spirit of not allowing the feasible ‘mixed good’ to defeat an unattainable ‘first best’. On this score, at least, the PRC study cannot be faulted. 2.2 The PRC Poverty Line Input (z) The World Bank’s international poverty line is pegged at $1.90 per person per day at 2011 Purchasing Power Parity Exchange (PPP) rates. The PRC study employs a poverty line of $2.00. (A discussion of the merits of this poverty line is deferred to a later stage.) From Table 2.4 of World Bank (2015) 5 , we find that $1 was equivalent, in PPP exchange terms, to ₹15.11 in 2011. An international poverty line of $2.00 would, therefore, translate to ₹30.22 per person per day, or, multiplying by 30 days, to ₹906.60 per person per month. This is taken to be the poverty line for both rural and urban India. Applying the Consumer Price Index of Agricultural Labourers (CPIAL), we obtain a rural poverty line of ₹1,478 per person per month at 2020 prices. Applying the Consumer Price Index of Industrial Workers (CPIIW), we obtain an urban poverty line of ₹1514 per person per month at 2019 prices. (The rural price index is estimated to have increased by a factor of 1.63 from 2011 to 2020, and the urban price index by a factor of 1.67 from 2011 to 2019: these factors are derived from RBI data on prices. 6 Our reconstruction of the poverty line ( z ) input data in the PRC study is summarised in Table 2: Table 2: Rural and Urban Poverty Lines per Person per Month (in ₹) in 2020 at Current Prices (PRC) Rural Poverty Line Urban Poverty Line 1,4781,514 Source: Author’s calculations. 2.3 The PRC Mean Incomes Input (m) Here is my reconstruction of the PRC methodology for deriving rural and urban ‘pre-COVID-19’ and ‘post-COVID-19’ means for 2020, on the basis of my interpretation of the methodology as outlined in Kochhar (2021). First, we note that the 68 Round NSO estimates of average per capita consumption expenditure in 2011-12, at 2011-12 prices, are: ₹1,287.17 for rural India, and ₹2,477.02 for urban India 7 . The PRC method consists, first, in using these estimates in the benchmark year, 2011-12, to estimate what their values might have been in 2019 if they had grown at the same rate as real per capita GDP over the period 2012 to 2019. World Bank data 8 suggest that India’s per capita GDP at constant local currency units increased by a factor of 1.4644 from 2012 to 2019: applying this growth factor to the 2011-12 NSO estimates of mean consumption yields rural and urban estimates for 2019 of ₹1,885.58 and ₹3,628.59 respectively, at 2011-12 prices. It remains to proceed from 2019 to 2020, which requires us to consider the World Bank’s projections in this regard. In January 2020 before the outbreak of the pandemic, the World Bank projected a growth rate of 5.8 per cent on the 2019 per capita GDP for 2020, which, in the light of the economic effects of the outbreak, was revised downward to (-) 9.6 per cent in January 2021. We can now envisage a counterfactual situation of what the rural and urban means might have been in 2020 in the absence of the pandemic, by applying the growth-rate of 5.8 per cent to the estimated 2019 rural and urban means of ₹1,885.58 and ₹3,628.59 respectively, to yield ₹1,994.94 and ₹3,839.05 respectively, at 2011-2012 prices. By applying the inflation factors, mentioned earlier, of 1.63 for the rural areas and 1.67 for the urban areas respectively, we can postulate the counterfactual ‘pre-COVID-19’ means, in 2020 prices, to be ₹3,251 (= ₹1,994.94x1.63) for rural India and Rs. 6410 (= 3839.05x1.67) for urban India. In similar manner, and after applying the growth rate of (-) 9.6 per cent to the 2019 estimates of means, followed by adjustment for inflation, we can obtain estimates of the ‘post-COVID-19’ means, in 2020, at 2020 prices, of ₹2,778 for rural India and ₹5,477 for urban India. Table 3 summarises what I take to be the PRC estimates of the rural and urban means in 2020, pre-and post-COVID-19: Table 3: Pre- and Post-COVID-19 Rural and Urban Average Incomes (in ₹) in 2020 at Current Prices (PRC) Pre-COVID-19 Rural Mean Post-COVID-19 Rural Mean Pre-COVID-19 Urban Mean Post-COVID-19 Urban Mean 3,2512,7786,4105,477 Source: Author’s calculations as indicated in text. 2.4 Results from the PRC Input Data I first summarise my reconstruction of the PRC study’s input data in Table 4. Table 4: Summary of PRC Study’s Reconstructed Input Data on Distributions, Poverty Lines and Means: 2020 Table-4page-0001jpg Source: Based on the numbers in Tables 1-3. The POVCALNET software programme returns the relevant headcount ratios, as furnished in Table 5, for the input data summarised in Table 4, from which one can calculate the changes in both the headcount ratios and aggregate headcounts attributable to the COVID-19 pandemic, separately for the rural and the urban areas. I have assumed an all-India population of 1,360 million for 2020, split between the rural and urban areas in the proportions of 65 per cent and 35 per cent respectively. Table 5: Levels and Changes in Headcount Ratios and Aggregate Headcounts Attributable to COVID-19, using the PRC Study’s Reconstructed Input Data Rural Pre-COVID-19 Rural Post-COVID-19 Rural Change Urban Pre-COVID-19 Urban Post-COVID-19 Urban Change Total Change HeadcountRatio.0723.1499.07760.0162.0162.0561 AggregateHeadcount(in millions)63.91132.5168.6007.717.7176.31 Source: Author’s calculations based on the input data summarised in Table 5. The incremental number of persons plunged into poverty by the COVID-19 pandemic is 76.31 million (final entry in Table 5), which tallies quite closely with the PRC study’s estimate of 75 million. Further comments are reserved for a later part of this note. We now attempt to reconstruct the APU study’s estimate. Return to Contents III. THE APU ESTIMATE The APU estimate of incremental poverty attributable to the COVID-19 pandemic is contained in the report State of Working India 2021: One Year of Covid (APU, 2021). This remarkable production is the third in a series on the ‘ State of Working India’ ; earlier reports having appeared in 2018 and 2019. The present (2021) edition places a special emphasis on the impact of and policy response to the COVID-19 pandemic. Work on these reports has been carried out under the coordination of a group of researchers in Azim Premji University’s Centre for Sustainable Employment (CSE). The engagement is with the condition of the labouring poor, and the 2021 report provides an extraordinarily detailed account of the general state of the economy, with a focus on lives, livelihoods, incomes, nutrition and living standards, as these have been affected by the pandemic, together with an analysis of policy response (mainly policy failure) and recommendations for meaningful government intervention. This report, and the series of which it is a part, will stand out as an exemplary model of the collection, collation, processing and analysis of data drawn from diverse sources, and of serious scholarly application, humane engagement, and committed effort in the cause of understanding the condition of India’s labouring poor. A particularly compelling measure of its worth is that the work in the report has been carried out in an environment of scanty and unreliable data, not to mention a generalised culture of official obfuscation and prevarication. Returning to our more immediate concerns, the APU study’s methodology is available in Chapter 5 of the State of Working India 2021 report, and is discussed, in what follows, with respect to the input data employed in the study. 3.1 The APU Income Distribution Input (D) The distributional data employed in the study are drawn from the Centre for Monitoring Indian Economy-Consumer Pyramid Household Surveys (CMIE-CPHS). What we earlier referred to as the ‘pre-COVID-19’ and ‘post-COVID-19’ periods correspond, in the APU study, to the eight-month period July 2019-February 2020 and the eight-month period March 2020-October 2020, respectively. The study accumulates the incomes in each income-class across the eight months in each period, to arrive at a consolidated picture of the ‘pre-COVID-19’ and ‘post-COVID-19’ distributions. These data are not explicitly presented in the State of Working India report but have been kindly made available to me by the report’s authors upon request. The relevant data are furnished in Table 6. Table 6: Pre- and Post-COVID-19 Rural and Urban Income Distributions (APU) Table-6page-0001jpg Note: G stands for the Gini coefficient of inequality. Source: Data supplied to the present author by the authors of the APU study. Some observations are in order. Surprisingly, (a) the APU estimates of the urban income-Gini in 2020 are slightly lower than the NSO urban consumption-Gini in 2011-12; and (b) there is only a minor suggestion of worsening of inequality from before to after COVID-19, in both rural and urban India. 9 Secondly, and as noted by the authors of the APU report, the earnings data in the CMIE-CPHS are substantially larger than those reported by the Periodic Labour Force Employment-Unemployment Survey of 2018-19. This issue will be briefly revisited later in this article. 3.2 The APU Poverty Line Input Data (z) The basis for the poverty lines employed in the APU study is explained thus in their report (APU, 2021: p.16): The Expert Committee on Determining the Methodology for fixing the National Minimum Wage (Ministry of Labour and Employment 2019) proposed a wage such that the expenditure on minimum recommended food intake, essential non-food items (namely clothing, fuel and light, house rent, education, medical, footwear, and transport) and other non-food items for the wage earner and their dependents can be met. The recommendation was ₹375 per day (₹104 per capita per day) for rural areas and ₹430 (₹119 per capita per day) for urban areas as of July 2018 10 . This works out to ₹2,900 per capita per month and ₹3,344 per capita per month respectively, after adjusting for inflation in Jan 2020 terms. The poverty line input data are summarised in Table 7. Table 7: Rural and Urban Poverty Lines per Person per Month (in ₹) in 2020 at Current Prices (APU) Rural Poverty Line Urban Poverty Line 2,9003,344 Source: APU (2021) Table 8, which combines data from Tables 2 and 7 shows that the APU rural and urban poverty lines are twice as large as the ones in the PRC study. This is a major source of deviation in the assessment of the impact of COVID-19 on poverty in India and calls for some discussion. Table 8: Rural and Urban Poverty Lines per Person per Month (in ₹) in 2020 at Current Prices (PRC and APU) Rural Poverty Line (in ₹) Urban Poverty Line (in ₹) PRCAPUPRCACU 1,4782,9001,514­­­­­­­3,344 Source: From Tables 2 and 7. 3.2.1 A pragmatic assessment of the poverty norm India’s official poverty lines are derived on the basis of that level of consumer expenditure at which some stipulated calorific norm of food consumption is found to be achieved in some reference year, and the reference year poverty line is then ‘updated’ for other years by means of a consumer price index to reflect price changes. The World Bank’s ‘dollar-a-day’ type poverty lines are based on the poverty lines of some of the income-poorest countries of the world many of which were prescribed by the World Bank itself.Neither approach is based on any explicit accounting of commodity requirements (and their costing) for achieving a well-defined list of human functionings at levels that might be deemed to just avoid deprivation. The result is that both official Indian poverty lines and the World Bank’s international poverty line have tended to understate the poverty threshold, by failing to provide a basis for these lines’ adequacy in the matter of meeting a set of basic needs in a measure that could be construed as necessary to escape poverty. The serious limitations of working with the World Bank’s international poverty line have been discussed by other commentators, including Reddy and Pogge (2010) and Reddy and Lahoti (2015), and will not be repeated here. Both official Indian poverty lines and the World Bank’s international poverty line have tended to understate the poverty threshold. What is suggestive is that often a combination of practical knowledge and common sense is a more reliable guide to identifying the poverty line than methods which involve plotting graphs and reading off threshold levels, or squinting at scatter diagrams of some of the poorest countries’ poverty thresholds. Most of us who are familiar with the environments in which we live must be expected to have a reasonably accurate idea of the income required to achieve some minimally acceptable standard of living.In the spirit of pragmatism just alluded to, Jayaraj and Subramanian (2017) have made an attempt to derive a poverty line for urban Tamil Nadu for the year 2014-15. In doing so, they consider both food and non-food necessities. Based on nutrient requirements and recommended dietary allowances for Indians as advanced by the Indian Council of Medical Research (2010) with reference to a low-cost ‘Indian vegetarian balanced diet’, the authors cost the items that might be expected to constitute the diet in question, while also taking account of the subsidiary ingredients that would typically enter a Tamil vegetarian diet of the type under consideration.In the matter of non-food requirements, they make essentially conservative estimates of what it would cost to achieve some elementary standard of living with respect to shelter, education, energy needs, healthcare, transport and communication, clothing and footwear, entertainment and socialization, and personal hygiene. The costing is done on a monthly basis for a family of five, and the poverty line which the authors come up with amounts to ₹14,000 for such a family, which most urban residents of India would view, from personal experience and practical knowledge, as a by no means unreasonable figure.On a per capita basis, the poverty line is a monthly income of ₹2,800—considerably higher than, for instance, the Rangarajan Committee’s recommended urban poverty line which, at 2014-15 prices, would be of the order of just ₹1,600. The poverty line suggested here is admittedly a rough-and-ready one, but it probably relates to what we know about poverty better than one assiduously derived from employing slide-rule-and-compass, which however bears little obvious relation to poverty as we might be expected to understand that condition.Continuing in this vein of uniform simple-mindedness, one could advance the cause of a poverty line (at 2014-15 prices) of ₹2,800 per person per month for urban India, and one for rural India of ₹2,240, which is 80 per cent of the urban poverty line: a swift (and brutal) concession to lower rural prices. Employing the CPIAL and CPIIW prices indices, the rural and urban poverty lines at 2020 prices are of the order of ₹2,839 per person per month for rural India, and ₹3,597 for urban India. These numbers are not far from the rural and urban poverty lines—₹2,900 and ₹3344 respectively—used in the APU study. The APU poverty lines surely appear to reflect a substantially more acceptable standard of what constitutes deprivation thresholds than the World Bank line adopted in the APU study (even allowing for the qualifier of ‘extreme’ for the poverty implied by the World Bank line). 3.3 The Mean Income Input (m) The APU study’s mean income estimates are based on a periodisation of pre- and post-COVID-19 India in two eight-month stretches—July 2019-February 2020 and March 2020-October 2020 respectively. The mean income for the pre-COVID-19 period is taken to be the average of the seasonally-adjusted monthly incomes from July 2019 to February 2020, and that for the post-COVID-19 period to be the average of the seasonally-adjusted monthly incomes from March 2020 to December 2020. The authors of the report state (APU, 2021: p.11):The seasonally-adjusted cumulative income in the months of March to October was 22 per cent less compared [with] the preceding eight months of July 2019 to February 2020. The cumulative decline was higher in urban areas than rural areas (26 per cent versus 21 per cent). For an average household in urban areas this amounts to losing 2.1 months of income (about ₹64,000 for a family of four) and in rural areas losing 1.7 months of income (about ₹34,000 for a family of four). From the quoted paragraph, one can infer 11 the magnitudes of the per capita monthly average income in the pre- and post-COVID-19 periods, for each of the rural and urban areas, and these are summarised in Table 9. Table 9: Pre- and Post-Covid Rural and Urban Average Incomes (in ₹) in 2020 at Current Prices (APU) Pre-COVID-19 Rural Mean Post-COVID-19 Rural Mean Pre-COVID-19 Urban Mean Post-COVID-19 Urban Mean 5,0603,9977,6925,692 Source: Based on APU (2021), as explained in the text. It is possible, as stated in Section 3.1, that the CMIE-CPHS estimates of income on which the APU study’s estimates are based are uniformly exaggerated versions of the corresponding actual incomes—arising possibly from under-sampling of the poorest classes (see Dreze and Somanchi, 2021). However, the declines in average incomes on account of the pandemic appear to be realistic in relation to what one knows about the differential impacts of the pandemic and the lockdown on rural and urban livelihoods in the context of employment and earnings. The APU estimate points to a substantial difference between declines in average urban and rural incomes. The decline in average urban income, at 26 per cent, is higher than the decline in average rural income, at 21 per cent. In contrast, the PRC study suggests a single, undifferentiated, and much lower reduction in average income of 14.6 per cent for both the rural and the urban areas (see Table 3). In view of this, and in view of the restricted choices available, there is a case for favouring the APU study-based estimates in Table 9. The case against what one might call uniform ‘data-nihilism’ is also made by Dhingra and Ghatak (2021) when they say: ‘Despite [certain] statistical concerns, the CPHS does provide consumption numbers for a large sample of individuals, which can provide insights into changes in consumption levels arising from the pandemic.’ 3.4 Results from the APU Input Data Table 10 summarises the reconstructed APU input data on distributions, poverty lines and mean incomes. Table 10: Summary of APU Study’s Reconstructed Input Data on Distributions, Poverty Lines and Means: 2020 Table-10page-0001jpg Source: Based on the numbers in Tables 7 and 9. Table 11, following, presents the POVCALNET results on headcount ratios, aggregate headcounts, and changes in these, for the input data on distributions, poverty lines and mean incomes attributed to the APU study. (As earlier, we take India’s 2020 population to be 1,360 million, with shares of 65 per cent and 35 per cent for the rural and urban areas respectively.) Table 11, relating to the ‘APU results’, corresponds to Table 5, which is a summary of the ‘PRC results’. Table 11: Levels and Changes in Headcount Ratios and Aggregate Headcounts Attributable to Covid-19, using the APU Study’s Reconstructed Input Data Rural Pre- COVID-19 Rural Post-COVID-19 Rural Change Urban Pre-COVID-19 Urban Post-COVID-19 Urban Change Total Change HeadcountRatio.2646.4187.1541.1631.3391.1760.1618 AggregateHeadcount(in millions)233.91370.13136.2277.64161.4183.77 219.99 Source: Author’s calculations based on the input data summarised in Table 10. The reconstructed APU data are compatible with an estimate of an increased aggregate poverty headcount, attributable to the COVID-19 pandemic, of 220 million—which falls short of the APU study’s estimate of 230 million, but not by much: the one estimate is nearly 96 per cent of the other. Return to Contents IV. DIFFERENCES BETWEEN THE PRC AND APU ESTIMATES Now, let us consider the incremental numbers of people pushed into poverty as a consequence of the pandemic and the accompanying lockdown. The APU estimate of this incremental number, at 230 million people, exceeds the PRC incremental estimate, at 75 million people, by a factor of 3! From what we know of the differential impacts of the pandemic-and-lockdown combination of events on rural and urban areas, it was the latter that were most severely affected. This is reflected in the reconstructed APU estimate which suggests that the incremental aggregate urban headcount (84 million) is about 38 per cent of the overall increase (220 million). The PRC estimate, on the other hand, suggests that the urban areas, with an additional (roughly) 8 million in poverty, account for less than 11 per cent of the overall change (76 million). This is not the only reason for judging the APU estimate as being vastly more plausible than the PRC estimate, as can be seen from the detailed evidence presented in the APU report on unemployment, job losses, losses in earnings, increased levels of hunger in the aftermath of the covid-inspired lockdown, and the extremely poor policy responses to these events of distress. In terms of the impact of the input data employed on the resulting outputs, it would appear that the distributions employed in the two studies were least instrumental in explaining the differing estimates of the two studies; differences in the mean incomes data employed by the two studies have greater explanatory significance; and differing assumptions about the poverty lines the greatest influence. Thus, if we preserve the APU data inputs on mean incomes and poverty lines but vary only the distributions by switching to those employed in the PRC study, we find that the resulting estimate of the change is 233 million: if anything, changing the distribution causes the estimate of the incremental change to increase , but not by much. If we preserve the APU data inputs on distributions and poverty lines but replace the APU mean incomes by the PRC mean incomes, we find a more substantial deviation in the change: it declines from 220 million to 147 million. Finally, if we preserve the APU data inputs on distributions and mean incomes but switch from the APU poverty lines to the PRC poverty lines, we discover a massive fall in the estimate: from 220 million to just 76 million. Our reservations on the widespread use of the World Bank’s international poverty line would seem to be well-founded: in the instant case, as in a general way, it is misleading to employ unrealistically low poverty lines, even when qualified by the notion of conveying a sense of ‘extreme’ poverty. Return to Contents V. CONCLUDING NOTE Everything considered, a count of upwards of 200 million additional people plunged into poverty, as estimated by the APU study, seems eminently plausible. We are speaking only of the first wave of the pandemic which, by all accounts, was less devastating than the second wave. The outcome, even when confined to a partial assessment of the impact on poverty, has been grievously harsh, accompanied, as it has been, by aspects of government policy that have been a combination of misplaced over-zealousness in the matter of implementing an abrupt, draconian lockdown and immutable reluctance in the matter of affording relief to the country’s affected citizens. A count of upwards of 200 million additional people plunged into poverty, as estimated by the APU study, seems eminently plausible. In this context, it is striking (even allowing for ‘adaptive expectations’) that we have not, apparently, had any state-sponsored attempt at providing or seeking evidence on the impact of COVID-19 on poverty. This is the more striking in the face of generalized and intense global awareness of, and concern with, the likely devastating consequences of the pandemic for national and international economic outcomes. Such engagement is easily seen in the research and opinion put out by various multilateral agencies such as the World Bank, the IMF and UNICEF, think-tanks like UNU-WIDER, professional journals like The Economist , and individual researchers. A small and illustrative list of studies on poverty and the pandemic would include: Kharas (2020), Kharas and Dooley (2021), Sumner et al (2020), Lakner et al (2021), IMF (2020), UNICEF (2020) (which contains both global and country-level studies on the impact of COVID-19 on child poverty in Africa, Europe and Central Asia, Latin America and the Caribbeans, South Asia, and East Asia and the Pacific), and several articles in The Economist (including in the issues of May 23, 2020; September 26, 2020; October 23, 2020; April 10, 2021; and May 15, 2021). The evidence on the impact of COVID-19 on living standards can be only as sound as the data on which it is based. But what evidence there is, combined with informed general awareness and the application of common sense, suggests both the need for and the possibility of well-founded policy intervention. This is a major reason why the available evidence needs to be appraised, systematised, and repeatedly put out in the public domain. Hence also this essay, however forlorn might be the hope that inspires it. Acknowledgement: The author is indebted to Amit Basole and Rahul Lahoti for very helpful comments on an earlier version of this essay . Return to Contents Also by the Author 1. Letting the Data Speak: Consumption Spending, Rural Distress, Urban Slow-Down, and Overall Stagnation, Dec. 11, 2019. 2. Some Basic Issues Underlying Basic Income, Feb. 7, 2019. 3. Some Views on Public Policy Outcomes in India - Is it the Message or the Messenger?, Nov. 12, 2018. [ S. Subramanian is a retired professor of Economics from the Madras Institute of Development Studies, and a former Indian Council of Social Science Research National Fellow. He has research interests in the fields of poverty, inequality, demography, welfare economics, social choice theory, and development economics. He is an elected Fellow of the Human Development and Capabilities Association, and was a member of the advisory board of the World Bank’s Commission on Global Poverty (2015-16). He is the author of, among other books, The Poverty Line (Oxford University Press: 2012), Inequality and Poverty: A Short Critical Introduction (Springer: 2019), and Futilitarianism (Routledge, Delhi: 2020). He can be contacted at [email protected] ]. Endnotes: 1. For a sample illustration, see the POVCALNET web-page titled ‘ Estimate Your Own Distribution’ , The World Bank here: [http://iresearch.worldbank.org/PovcalNet/PovCalculator.aspx]. Return To text. 2. Just for completeness of record, here is how the input data are converted into the corresponding output results. (This methodological summary can be ignored by the general reader without any significant loss in the narrative of this Issue Brief.) The distributional data, D , are essentially in the form of distinguished ordinates of the Lorenz curve , and there is a software programme which uses these data to estimate the equation of the Lorenz curve; once that is done, it is a simple matter to derive the value of the Gini coefficient of inequality, which is just twice the area enclosed by the Lorenz curve and the diagonal of the unit square in which the curve is plotted. As for the headcount ratio, the software programme exploits the fact that the slope of the Lorenz curve at any point corresponding to an income level of x is just x/m , where m , to recall, is mean income; so the headcount ratio of poverty can be inferred as that value on the Lorenz curve’s horizontal axis at which the slope of the Lorenz curve (computable from the already derived equation of the Lorenz curve) is equal to z/m , z being, of course, the poverty line. The POVCALNET software resorts to two estimating equations of the Lorenz curve—the so-called General Quadratic Lorenz and the Beta Lorenz. All estimates in this note are based on the relevant General Quadratic Lorenz’s. Return to Text. 3. Household consumption expenditure is “the sum total of monetary values of all the items (i.e. goods and services) consumed by the household on domestic account during the reference period.” Expenses that are actually made only on consumption are included, and therefore, imputed expenses, such as rents of owner-occupied houses, or expenses incurred on productive enterprises are excluded. (Summarised from ‘ India - Household Consumer Expenditure, Type 1 : July 2011 - June 2012, NSS 68th Round ’, Technical Documents, Concepts and Definitions, P A-11.) [http://microdata.gov.in/nada43/index.php/catalog/1/related_materials]. Return to Text. 4. The URP method refers to consumption data collected by asking “people about their consumption expenditure across a 30-day recall period” Under MRP, “data on five less-frequently used items are collected over a one-year period, while sticking to the 30-day recall for the rest of the items. The low-frequency items include expenditure on health, education, clothing, durables etc.” Under MMRP “for some food items, instead of a 30-day recall, only a 7-day recall is collected. Also, for some low-frequency items, instead of a 30-day recall, a 1-year recall is collected. This is believed to provide a more accurate reflection of consumption expenditures.” Misra, U. 2015 . “ Meaning URP, MRP, MMRP “, The Indian Express, October 7. [https://indianexpress.com/article/explained/meaning-urp-mrp-mmrp/]. Return to Text. 5. World Bank. 2015 . Purchasing Power Parities and Real Expenditures of World Economics: A Comprehensive Report of the 2011 International Comparison Program , Washington, DC. © World Bank . [https://openknowledge.worldbank.org/handle/10986/20526]. License: CC BY 3.0 IGO. Return to Text. 6. For data on CPIAL, see https://rbi.org.in/scripts/BS_ViewBulletin.aspx?Id=13884 for 2011-12, and https://rbi.org.in/scripts/BS_ViewBulletin.aspx?Id=20342# for April 2020; and for data on CPIIW, see https://rbi.org.in/scripts/BS_ViewBulletin.aspx?Id=13882 for 2011-12, and https://rbi.org.in/scripts/BS_ViewBulletin.aspx?Id=18666 for October 2019. Return to Text. 7. Tables 1BR and 1BU of National Sample Survey (2014): Level and Pattern of Consumer Expenditure 201-12 , NSS 68 Round, National Sample Survey Office, MOSPI, GOI, February 2014. Return to Text. 8. The World Bank . nd . GDP per capita (constant LCU) – India . [https://data.worldbank.org/indicator/NY.GDP.PCAP.KN?locations=IN]. Return to Text. 9. Note: However, in both cases, for each cumulated decile of the population, the cumulated income share in the pre-COVID-19 period is greater than or equal to the corresponding cumulated income share, post-COVID-19, reflecting a case of what in the technical literature is called ‘Lorenz dominance’. Return to Text. 10. I take it that the recommended daily rural and urban allowances of ₹375 and ₹430, respectively, are for a household of four, so that the daily per capita allowances become ₹93.75 (or ₹2,812.50 per month) and ₹107.50 (or ₹3,225 per month) at 2018 prices. The reported daily allowances of ₹104 and ₹119 translate to monthly levels of ₹3,120 and ₹3,570 respectively at 2018 prices, in excess the poverty lines for 2020 specified in the Report. One suspects there is an error in reporting the daily per capita allowances. Return to Text. 11. For example, for the rural areas, a 21 per cent loss of ₹34,000 suggests pre-and post-COVID-19 incomes of ₹161,905 (= 34000/.21) and ₹127,905 (= 161,905 – 34,000); on a per capita basis, given a family of four, this works out to ₹40,476 and ₹31,976 respectively; averaging out over eight months, yields per capita monthly means for the pre- and post-COVID-19 periods of ₹5,060 and ₹3,997 respectively. Similar computations can be made for urban areas. Return to Text. References: [ All URLs were last accessed on August 17, 2021. ] Azim Premji University. 2021. State of Working India 2021: One year of Covid-19 , Centre for Sustainable Employment. [https://cse.azimpremjiuniversity.edu.in/wp-content/uploads/2021/05/State_of_Working_India_2021-One_year_of_Covid-19.pdf]. Dhingra, S. and Ghatak, M. 2021. ‘ How has Covid-19 affected India’s economy? ’, Economics Observatory . [https://www.economicsobservatory.com/how-has-covid-19-affected-indias-economy]. Dreze, J. and Somanchi, A. 2021. ‘ The Covid-19 Crisis and People’s Right to Food ’, SocArXiv. June 1. doi:10.31235/osf.io/ybrmg. [https://osf.io/preprints/socarxiv/ybrmg/]. Indian Council of Medical Research. 2010. Nutrient Requirements and Recommended Dietary Allowance for Indians: A Report of the Expert Group of the Indian Council of Medical Research 2010 , National Institute of Nutrition, Hyderabad, India. [https://www.enacnetwork.com/files/pdf/ICMR_RDA_BOOK_2010.pdf]. International Monetary Fund. 2020 . ‘ A Crisis Like No Other, An Uncertain Recovery ’, World Economic Outlook Update, June 2020. [https://www.imf.org/en/Publications/WEO/Issues/2020/06/24/WEOUpdateJune2020]. Jayaraj, D. and Subramanian, S. 2017. ‘The Iniquity of Money-Metric Poverty in India’, Basic Income Studies , 12 (1): pp. 1 – 26. Kharas, H. 2020. ‘ The Impact of Covid-19 on Global Extreme Poverty ’, Brookings , October 21. [https://www.brookings.edu/blog/future-development/2020/10/21/the-impact-of-covid-19-on-global-extreme-poverty/]. Kharas, H. and M. Dooley, M. 2021. ‘ Long-Run Impacts of Covid-19 on Extreme Poverty ’, Brookings , June 2. [https://www.brookings.edu/blog/future-development/2021/06/02/long-run-impacts-of-covid-19-on-extreme-poverty/]. Kochhar, R. 2021. ‘ In the pandemic, India’s middle class shrinks and poverty spreads while China sees smaller changes ’, Pew Research Centre , March 18. [https://www.pewresearch.org/fact-tank/2021/03/18/in-the-pandemic-indias-middle-class-shrinks-and-poverty-spreads-while-china-sees-smaller-changes/]. Lakner, C., Yonzan, N., et. al. 2021. ‘ Updated Estimates of the Impact of Covid-19 on Global Poverty: Looking Back at 2020 and the Outlook for 2021 ’, World Bank Blogs, January 11. [https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty-looking-back-2020-and-outlook-2021]. (An updated analysis by the same authors is available at ‘ Updated estimates of the impact of COVID-19 on global poverty: Turning the corner on the pandemic in 2021? ’, World Bank Blogs, June 24.) [https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty-turning-corner-pandemic-2021]. Ministry of Labour and Employment. 2019. Report of the Expert Committee on Determining the Methodology for Fixing the National Minimum Wage , Government of India. [https://labour.gov.in/sites/default/files/Commitee_on_Determination_of_Methodology.pdf]. Reddy, S. and Lahoti, R. 2016. ‘$1.9 a Day: What Does it Say?’ New Left Review , Jan-Feb 2016, 97: 106-127. Reddy, S. and Pogge, T. 2010. ‘How Not to Count the Poor,’ in S. Anand, P. Segal and J. Stiglitz (eds): Debates on the Measurement of Global Poverty, Oxford University Press: New York. Sumner, A., Hoy, C., et. al. 2020. ‘ Estimates of the Impact of Covid-19 on Global Poverty ’, WIDER Working Paper No. 2020/43, April. [https://www.wider.unu.edu/sites/default/files/Publications/Working-paper/PDF/wp2020-43.pdf]. UNICEF. nd. Covid-19 Impacts on Child Poverty: Social Policy Analysis to Inform the Covid-19 Response . [https://www.unicef.org/social-policy/child-poverty/covid-19-socioeconomic-impacts].

In the space of two weeks in July, two decisions resurrected the policy focus on cooperatives in India. The first, by the executive, was to constitute an independent Union Ministry of Cooperation (MoC). The second, by the judiciary, was a verdict of the Supreme Court of India declaring that cooperative societies as a subject matter belong “wholly and exclusively to the State legislatures to legislate upon”. In this Issue Brief, H.S. Shylendra, Professor, Social Science Area, Institute of Rural Management (IRMA), Anand, draws out the legal and constitutional implications of these two developments, presents the relevance of a cooperative-based economy, and identifies the pathways for its success in the light of India’s experience with cooperatives and the prevailing political economy. The best prescription, he concludes, would be a movement, more than a ministry, to support India’s ailing cooperative sector proactively in diverse ways without hurting its autonomy. CONTENTS I. INTRODUCTION II. BRIEF HISTORY LEADING TO A MINISTRY III. ‘EMBRACE-OF-DEATH’ TO REFORMS IV. BUILDING A COOPERATIVE-BASED ECONOMY V. PATHWAYS TO COOPERATIVE SUCCESS I. INTRODUCTION Two recent developments have brought the policy focus back on India’s cooperatives. The first is the decision of the Government of India (GoI) on July 6, 2021, to constitute an independent Union Ministry of Cooperation (MoC) and the second is the judgement of the Supreme Court of India delivered on July 20, 2021, declaring that “Co-operative societies as a subject matter belongs wholly and exclusively to the State legislatures to legislate upon...” 1 Coming as they did from different sources, these two decisions have clear consequences on each other. The creation of the MoC has raised hackles over the real intention of the Union government as it is perceived to open out space for the centre to interfere in the working of the cooperatives that are under the jurisdiction of State governments. The Supreme Court judgement on a writ appeal on the 97 th Constitutional Amendment Act (CAA) clarifies the constitutional position on the domain over cooperatives and by virtue of that gives credence to the concerns of the States over possible meddling by centre in their domain, 2 be it through amendments to the law or by creating a Ministry. The newly established MoC has also raised a debate over the potential role such a Ministry can play in promoting the cooperative sector given the current socio-economic milieu. The Government of India on its part has called the step an ‘historic move’ that will strengthen cooperatives as a true peoples’-based movement. The government in its press note 3 has emphasised that a ‘Co-operative based economic development model is very relevant....’ and the Ministry through its ‘administrative, legal and policy framework’ will streamline the processes of ‘Ease-of-doing-business for cooperatives.’ Thus, apparently, the Ministry has set a larger goal for itself of working towards a cooperative-based-economy through a multi-pronged strategy. Those supportive of the new idea feel that it can help bring about uniform development of the cooperative movement in the country given its uneven spread 4 and address the much-needed inter-State coordination in the working of cooperatives 5 . However, sceptics are clear that in addition to compromising on the norms of federalism, the Ministry may work more as a front for dispensing political patronage 6 . Given such mixed concerns, it would be worthwhile to examine critically not only the legal position of such a Union Ministry but also the larger issue of promoting a cooperative-based-economy. Return to Contents II. BRIEF HISTORY LEADING TO A MINISTRY In the constitutional scheme of things, a clear demarcation has been drawn regarding cooperatives by placing them in the State List (List II of Seventh Schedule). The States have exclusive powers to legislate on and govern the cooperatives registered within their boundaries. Although the first cooperative societies act passed in 1904 under the colonial rule (and amended in 1912) was a central act, the 1919 administrative reforms transferred cooperatives to the provinces (GoI 2005) 7 . Since then Provinces and, after Independence, States have taken over the subject of cooperatives and have framed their own Acts to regulate cooperatives. In the meanwhile, the Multi-Unit Co-Operative Societies Act, 1942, was passed by the Government of India in 1942 (re-enacted in 1984 and 2002) giving the Union government jurisdiction over multi-State cooperatives. Overall, since the first Act of 1904, there has been a fair amount of clarity about the jurisdiction of the Union and the State governments over cooperatives, although the Reserve Bank of India as a federal level monetary authority could exercise some powers over the cooperative banks especially in the interest of the depositors as per the Banking Regulation Act 8 . Having been assigned primacy over cooperative governance, State governments created a separate ministry or department of cooperation for administering the cooperatives. Given the importance of this sector, State-level cooperative Ministries have also enjoyed a fair amount power and autonomy. The Government of India on its part has been working with cooperatives mainly through a minor department created as a part of some major Ministry to discharge its responsibilities pertaining to multi-state cooperatives and the general development of cooperatives in the country through various developmental schemes. Since 1904, there has been clarity about the jurisdiction of the Union and the State governments. The developmental role pursued by the Union government includes promotion of cooperatives, provision of financial assistance, capacity building through training of members and staff, infrastructure and technology development, and revival plans. Such schemes, framed under the Five Year Plans, were implemented through the concurrence of the respective State’s cooperative ministry or department. Given this two-fold role, over the years the cooperative department has been attached to or placed with diverse Union ministries such as food and civil supplies or community development or commerce or agriculture. Such linkages with a multiplicity of Ministries underscore the broader scope of the cooperative sector, combining both agriculture and non-agricultural cooperatives. Given that agriculture has been the prominent sector for cooperatives, since 1979 the Department of Cooperation has been attached to the Union agricultural ministry. Until the creation of the new MoC, issues pertaining to cooperatives were overseen by a division within the Department of agriculture, cooperation and farmers’ welfare coming under a larger ministry for agriculture 9 . Hence, the sudden up-gradation of a division/department with a relatively limited role into a full-fledged Union Ministry is a curious development, triggering concerns. An argument being put-forth is that the cooperative division in the agricultural department was unable to look after adequately the cooperatives, more so with regard to such entities operating in the non-agricultural sector which in the recent days constitute a significant proportion 10 . However, even if the non-agricultural cooperatives have grown in numbers, a bulk of them are working under the jurisdiction of State governments (see Table 1). Such an argument, hence, may not be fully tenable. Explicating New Delhi’s rationale for such a step and clarifying the concerns of the cooperative stakeholders would require going beyond the mere legal or administrative angle. Such an explanation is attempted in the following section which highlights the issues connected with the larger politics and governance about the cooperatives, and the likely compulsions that may have arisen in the sector in context of the economic reforms. Table 1: Sector-wise Distribution of Cooperatives in India (%, 2016-17) Sector % (Total in numbers) Credit & Thrift20.79 Housing17.83 Dairy17.79 Labour5.50 Agri-Allied & Livestock3.50 Consumer3.08 Women/Tribal/SC&ST2.52 Textile & Handloom2.05 Industrial2.03 Multi-Purpose1.75 Others23.02 Multi-State Coops0.15 Total Cooperatives (number) 8,54,355 Source: National Cooperative Union of India (NCUI), 2018 . Return to Contents III. ‘EMBRACE-OF-DEATH’ TO REFORMS India’s first Prime Minister, Jawaharlal Nehru, who wanted to ‘convulse India with Co-operation’ was equally emphatic that government control over cooperatives is like an ‘embrace-of-death’ (as quoted in Dwivedi 1989). 11 Cooperatives, which are democratic institutions by form, have been treated as potential training grounds for developing and nurturing grassroots leaders who can then move into the larger political domain. Given the competitive politics over the decades, this double-edged intention, howsoever noble, unfortunately has degenerated into a wily strategy of political parties and leaders to capture cooperatives to advance their own prospects in the guise of cooperative development. The sector has emerged as an avenue for dispensing patronage to the supporters of ruling parties. Ruling parties and the governments have openly made use of such opportunities to seize positions or suspend the committees of opposing groups or appoint bureaucrats to run the cooperatives under the tutelage of a government department (GoI 2009) 12 (Jain and Coelho 1996) 13 . No doubt in several places, irrespective of political opportunities which were there for the taking at local or regional levels, many leaders have worked more broadmindedly and in a neutral manner to develop cooperatives as successful ventures for the benefit of the wider section of the membership. Given the developmental role assigned to cooperatives under the planning process and the resources deployed for the purpose, the cooperatives sector has emerged as an avenue for dispensing patronage to the supporters of ruling parties, either by way of nomination to the governing boards or sanctioning schemes specific or common to the cooperatives. The policy of contributing to the share capital of the cooperatives and providing various financial assistance like loan and guarantees have enabled State governments, in the name of public interest, to directly intervene in the working of cooperatives which are legally autonomous. The role of the State governments has only worked to the detriment of the cooperative movement in general despite leading to some localised successes (Baviskar and Attwood 1991) 14 . Such a top-down approach deprived the cooperatives of their vitality in meeting the needs of their members and losing credibility in the process. The prevailing social-economic inequalities as reflected in illiteracy, poverty, and caste-differences also had not helped the cause of the cooperatives. Horace Plunkett, the pioneer of Irish cooperatives, had aptly observed: ‘there is no cooperative movement in India, there is only the cooperative policy of government’ 15 . The poor outcomes of the state-driven interference in the cooperative movement and the emerging realities in the post-reforms era resulted in some serious policy level introspections about the cooperatives. Given also their structural constraints related to scale of operations and ability to access capital, cooperatives had struggled to thrive in the liberalised economy despite growing in physical numbers (see Table 2). For example, the share of credit cooperatives in the ground level credit disbursed which was 62 per cent in 1992-93 plummeted to 34 per cent in 2002-03 16 . Table 2: Progress of Cooperatives Indicator 1950-51 17 1991-92 2016-17 Total Number 181190318700854355 Total Members (Million)13.7148.0290.1 % of members to total population3.8 %17.5%22.2% Source: NCUI, 2018. Although the cooperative sector had shown some hesitancy to accept economic reforms, the emerging realities forced them and the government to evolve relevant strategies to face up to the challenge. Simultaneously, there were strident calls to give autonomy to cooperatives to function more independently and to respond adequately to the signals of a market-economy. Reforming cooperatives assumed greater importance under the ongoing economic liberalisation. Some of the reforms initiated included opening-up the dairy sector to players other than cooperatives, application of prudential norms to cooperative banks, and enactment of liberal cooperative Acts by the States. Many civil society organisations had already started organising collectives outside the cooperative laws in the form of trust or societies to avoid state control. There were also efforts to form informal cooperatives and self-help groups (SHGs) under the growing influence of the design-principles based on institutional economics (Agarwal 2010). 18 Many cooperative leaders wanted more liberal cooperative laws. This came in the form of the enactment of the mutually aided cooperative society Acts starting from 1995 onwards by seven State governments. Andhra Pradesh was the pioneer which had passed The Andhra Pradesh Mutually Aided Co-operative Societies Act, 1995, considered as a path-breaking law. These new liberal laws encouraged formation of cooperatives delinked from the government patronage and control. The second major legal measure was the amendment in 2002 to the Companies Act of 1956, to create a new kind of cooperatives called Producers’ Companies’ (PCs) as hybrid organisations combining the strengths of cooperatives and the corporate entities. At the same time, given the growing prominence of multi-state cooperatives in terms of their number and business, the Union government came up with a more enabling legislation called the Multi-State Cooperative Societies Act in 2004, replacing the 1984 Act 19 . The next major step in the direction was the enactment of the 97 th CAA in 2012, which conferred a fundamental right on formation of a cooperative, and introduced, to quote from the Statement and Objects of the Bill, “fundamental reforms to revitalize these institutions in order to ensure their contribution in the economic development of the country and to serve the interests of members and public at large and also to ensure their autonomy, democratic functioning and professional management.” 20 A major reason attributed by the Union government to justify the CAA was that despite incentivising institutional and legal reforms through cooperative revival schemes, State governments were not forthcoming proactively to change the legal framework because of their own compulsions (GoI 2009) 21 . State governments, hence, were to be compelled to change their laws in tune with uniform constitutional norms. Incidentally, it is these uniform provisions of the 97 th CAA which the Supreme Court has struck down in its judgement of July 20, 2021, in their application to States whose concurrence was not taken for the same. It is now left to the State governments to decide whether they would like to retain or not the amendments made in their cooperative Acts pursuant to the 97 th CAA. Thus, both the Union and the States have made several attempts in the post-reforms period to restructure the cooperative legal framework with mixed outcomes. The former, particularly, has taken legal and constitutional measures to alter the governance scenario despite cooperatives being prominently in the State domain. In the process, while the centre saw the States as reluctant reformers, it was, in turn, perceived by States as obtruding in the guise of reforms. This gives a clear perspective as to why the formation of a new MoC is contentious, if not untenable. The State governments, in particular those ruled by opposition parties, are bound to perceive that Union government may have some other plan up its sleeve. Although part of provisions of the 97 th CAA pertaining to State-level cooperatives have been struck down by the Supreme Court, the role of Union government regarding multi-state cooperatives has been clearly recognised. The developmental role of the centre continues to be relevant even as the legal forms of cooperatives have been getting diversified. In addition, more women are coming forward to be part of the cooperative movement. The centre, no-doubt, has a prerogative to restructure its administrative framework to streamline its activities. The formation of the MoC is legally and constitutionally tenable even though the up-gradation looks disproportionate to the current level of engagement of the Union government with the cooperative sector. However, it may want to play a bigger role proactively going beyond the current mandate given the potential that the cooperative sector holds for building political constituencies. According to a newspaper report, the centre may even explore amending the Constitution to add cooperatives in the Concurrent List to enhance its mandate more legitimately 22 . The press note issued about the MoC, however, does not clarify many of these issues except identifying some hazier goals including talking about the relevance of cooperative-based economic development. Given the common interests that are at play, the Union Government’s apparent keenness to play a larger role in the cooperative sector can become relevant provided it can come out clearly with its plan and seek the cooperation of the States. In India’s federal structure, establishing partnership with the States becomes necessary for this new Union Ministry to work towards building a cooperative-based economy that it has visualised. Return to Contents IV. BUILDING A COOPERATIVE-BASED ECONOMY The real challenge of building a cooperative-based economy, however, lies in making cooperatives thrive on a wider basis, assuming that the Union and the States would be working together for such a cause. The more pertinent question, however, is: How to build a cooperative-based economy in a system which is moving towards strong capitalism? A cooperative-based economy could be defined as one where all major economic activities are prominently carried out by cooperatives and that cooperative way of life is the norm in the society. An overbearing state did not help as cooperatives lost autonomy and got excessively politicised. India’s efforts under the Five Year Plans in the post-independence period hold some lessons here. The planning era started with the goal of creating ‘Cooperative Socialism’ with the thrust being on ‘cooperativising the rural economy’ along Gandhian lines. The state had adopted a proactive approach to support cooperatives through various means. Given the fact that the economy was in a nascent stage of development, cooperatives were able to make some dent in sectors such as credit, milk, sugar, and fertilizers. The policy of favouring cooperatives in some of these sectors helped them grow significantly. Cooperatives in the dairy and sugar sectors succeeded to a considerable extent due to adoption of integrated models, which helped control the value chain and ensure member loyalty through assured price and services (Attwood and Baviskar 1988) 23 (Shah 1996). 24 However, despite some pockets of success, cooperativisation could not go the desired extent. As identified earlier, the overbearing nature of the state did not help the cause either as the field not only lost autonomy but got excessively politicised as well. Moreover cooperatives, in general, suffered from other factors that have a bearing on their sustainability, such as constraints in achieving scale, lack of professional support and lack of adequate capital. Inter-group conflicts and domination by local elite were also found to be common among cooperatives. The arrival of reforms in the 1990s only exacerbated the inherent challenges. Private enterprises entered sectors such as dairy, sugar, and credit that were earlier dominated by cooperatives. Having lost some of their advantages and in the absence of any level playing field, cooperatives faltered despite growing in numbers. Resilient cooperatives and those operating in certain sectors such as fertilisers, milk, sugar, and textiles managed to retain some significant share (Table 3), albeit dwindling over the years 25 . Much of the market share in all the sectors currently is held by entities other than cooperative enterprises. Cooperatives overall play only a minor role in economies like India. A global survey conducted for the United Nations in 2014 (Dave Grace & Associates 2014) 26 revealed that cooperatives’ gross revenue to GDP in Asia was 3.25 per cent as against 7.08 per cent for Europe and 4.12 per cent for North America. Table 3: Sector Specific Share (%) of Cooperatives (2016-17) Sectors % Agri-Credit13.4 Fertilizer Production28.8 Fertilizer Distribution35.0 Sugar Produced30.6 Milk Procurement17.5 Storage Capacity14.8 Spindleage29.3 Direct-Employment13.3 Source: NCUI (2018) Given such a situation, it would be an enormous challenge for cooperatives to regain their position and relevance. The mere slogan ‘ Sahakar se Samruddhi’’ (prosperity from cooperation) of the MoC may not help unless a radical shift takes place in the situation of the cooperatives supported by right kind of ideology and policy stance. As a policy, the announcement of MoC by the present government comes off as one that is more spontaneous like the Atmanirbhar Bharat (self-reliant India) launched in the wake of the COVID-19-induced economic crisis. Both steps – the formation of the MoC and self-reliant India – are inherently contradictory to the stated policy position and ideological commitments of the main ruling party. The present administration is committed more to globalisation and neoliberal reforms to deepen the capitalist footprints in the country based on private investment and entrepreneurship. A careful reading of the NITI Aayog’s two policy documents viz. ‘The Three-Year-Action Agenda:2017-20’ (NITI Aayog 2017) 27 and ‘Strategy for New India@75’ (NITI Aayog 2018) 28 clearly brings out that cooperatives are nowhere in the picture of making India a $4-trillion-economy by 2022-23, as visualised in the strategy. Even in the agricultural sector, where cooperatives have conventionally played a significant role in some of the fields, there is focus mainly on the private investment to promote agribusiness as a way of resolving the agrarian crisis involving a majority of the small and marginal farmers. One can see only a perfunctory mention of cooperatives or farmers’ producer organisations (FPOs) to play a peripheral role. The cooperatives which had struggled to blossom even in the heydays of planning are bound to shrivel in an era devoid of any ideological heft. Creation of a new ministry hence sounds rhetorical being not backed up by relevant policy and ideology to make any significant dent. Return to Contents V. PATHWAYS TO COOPERATIVE SUCCESS Apart from the ideological conviction, real pathways to the success of cooperatives would go with the following strategies. Cooperatives, despite their varied global success, remain relevant from the point of view of human welfare. Their social and economic relevance has been recognised even in capitalist economies, while they have played a significant role as part of the planning process in socialist economies. The social significance of cooperatives emerges both due to their intrinsic value and the instrumental role they can play in overcoming the social and economic crises wrought by capitalism. Solidarity among humans has become essential in view of growing challenges like alienation, atomism, inequality, and ecological rift (Ray 2021). 29 The logic of capitalism based on profit-maximisation and accumulation is at the root of many of these crises. As suggested by Marcel Mauss, “[c]ooperative economic organisations guarantee the perpetuation of the future society” (quoted in Nash et.al. 1976,p 3). 30 Economically, cooperatives offer several advantages although they come along with certain inherent limitations. The first advantage is that they enable members with small means to reap the benefits of collective action. In the absence of such a scope, the poor and disadvantaged become highly vulnerable to potentially exploitative market forces. Cooperatives offer bargaining strengths to withstand such vulnerabilities and obtain needy services at cost (Roy 1981). 31 This is the primary reason as to why cooperatives are strongly advocated for the poor (Shylendra 2013). 32 Similarly, for certain perishable commodities or areas crucial for livelihoods such as milk, vegetables, microcredit, and natural resources, cooperatives are seen as the ideal form of business because they enable easier mobilisation of members with scope for scale and cost reduction. Workers’ cooperatives are another sector of high relevance and advantage. Moreover, given their focus on mutual benefit over profit, cooperatives can help moderate monopolistic tendencies to ensure fair prices and practices. This is one of the primary reasons as to why cooperatives have grown in strength even in capitalist economies. For example, cooperative membership in Europe and North America accounted for 45.6 per cent and 38.6 per cent of the population respectively (Dave Grace & Associates 2014) . Thus, both socially and economically, cooperatives have merits justifying their relevance in any form of economy. Their social and economic relevance has been recognised in capitalist and socialist economies. State and civil society must support cooperatives proactively in diverse ways through suitable law, education, finance, technology, and policies without hurting their autonomy. The best prescription for ‘good governance’ in cooperatives is to promote cooperatives actively without compromising on their basic principles. In addition to such a proactive approach, efforts must be made to help cooperatives overcome some of their structural limitations in attaining the required scale and viability.New ways of organising cooperatives must be necessarily evolved to ensure their economic success. The inconsiderate aim of forming an independent and formal cooperative for every village or local habitation, irrespective of size, has embedded a structural hindrance to achieve the needed scale for many of the cooperatives. Hence, many cooperatives at the primary level remained unviable. Efforts to revive them through amalgamation or capital infusion has been ridden with difficulties given the top-down approach of such polices. If a cooperative remains unviable, it faces challenges of credibility and sustainability of services. The primary unit need not necessarily be a stand-alone cooperative unit always. In case of size constraint, it should try and function more as a branch of a larger unit to economise. In other words, there can be a multi-village cooperative working as a hub for remote villages having branches. One related possibility in this direction is careful selection and prioritisation of sectors and areas for cooperative formation. Although cooperatives may be organised for specific commodities or services, wherever relevant and feasible, multi-purpose cooperatives could be organised to attain viability. In recent days a cluster-based approach is being advocated, including adoption of ‘one-district-one-crop’ for FPOs. However, both may work in a top-down way, resulting in the exclusion of many producers and crops falling outside such a design. The attempt should be to include all potential members needing service in the jurisdiction and overcome viability challenge through innovative design. Again, the commonly advocated three-tier structure for all cooperative sectors need not be imposed in a top-down way. A multi-tier cooperative structure may evolve more organically as per its economic need to enable control over the value chain as well as to have clear division of functions at different levels of integration. Such integration of cooperatives into a multi-tier system must necessarily be promoted on the principle of democratic federalism which respects the mutual autonomy and accountability of each tier. Legally, cooperatives may assume any form at different levels provided they adhere to basic cooperative norms and are not discriminated by policies because of their legal form.Another crucial area which is often neglected is the professional support for cooperatives to work efficiently in the competitive environment. Apart from having their own professionals trained for their needs, cooperatives must be enabled to access, in innovative ways, the support of empathetic professionals and technical services through collectives or social enterprises which are organised specifically for such services.Agriculture, which is afflicted by growing fragmentation of operational holdings and ridden with innumerable crises, continues to remain a sector that is ripe for a vibrant revival movement to organise collectives. The efforts to build a cooperative-based economy can start with agriculture and extend to other sectors logically, as advocated by the late V. Kurien, the founding Chairman of the Gujarat Cooperative Milk Marketing Federation (GCMMF), which is popular internationally as Amul. To conclude, a cooperative-based economy is the need of the times and is worthy of serious consideration, more so in the economic and social world which will emerge after COVID-19, which has put enormous pressure on existing business models. What is required is a more coordinated and planned effort involving various levels so that cooperatives can re-emerge in a bottom-up way to grow into viable and valuable social enterprises. What India needs is a real movement for cooperatives than the mere creation of a Ministry of Cooperation. Return to Contents [ H.S. Shylendra is Professor in the Social Science Area, Institute of Rural Management, Anand (IRMA). His areas of interests include Development Theories, Rural development, Gender, Local Governance, and Cooperatives. He has nearly three decades experience combining research, teaching, policy engagement and academic administration. He was a member of the Reserve Bank of India’s Expert Committee on Credit Cooperatives. He can be contacted at [email protected] ]. Endnotes: 1. Supreme Court of India. 2021. “ Union of India v. Rajendra N. Shah “, p.38, Civil Appeal Nos.9108-9109 of 2014, July 20. [https://main.sci.gov.in/supremecourt/2013/21321/21321_2013_32_1501_28728_Judgement_20-Jul-2021.pdf]. Last accessed on August 3, 2021. Return To text. 2. Economic and Political Weekly . 2021. “ A New Ministry for Cooperation “ , Vol. 56, Issue. 30, July 24. [https://www.epw.in/journal/2021/30/editorials/new-ministry-cooperation.html?0=ip_login_no_cache%3D9c8b8f0e47df5cfc4513a1b7d579a36d]. Last accessed on July 27, 2021. Return to Text. 3. Cabinet Secretariat. 2021 . “ Modi Government creates a new Ministry of Co-operation “, Posted by PIB Delhi, July 6. [https://pib.gov.in/PressReleasePage.aspx?PRID=1733225]. Last accessed on July 23, 2021. Return to Text. 4. Biswas, P. 2021 . “ Explained: Why a Ministry of Cooperation “, The Indian Express , July 15. [https://indianexpress.com/article/explained/explained-why-a-cooperation-ministry-7395784/]. Last accessed on July 23. Return to Text. 5. Gulati, A . 2021 . “ What the new Ministry of Cooperation needs to achieve “, The Indian Express , July 19. [https://indianexpress.com/article/opinion/columns/new-ministry-of-cooperation-agenda-pm-modi-7410968 / ]. Last accessed on July 23, 2021. Return to Text. 6. Rajashekhar, M. 2021 . “ Why Exactly Did India Need a Brand New Ministry for Cooperatives, With Amit Shah As Head? “, The Wire , July 11. [https://thewire.in/government/ministry-for-cooperatives-amit-shah-bjp-nda-narendra-modi]. Last accessed on July 23, 2021. Return to Text. 7. Government of India. 2005 . “Report of the Task Force on Revival of Rural Co-operative Credit Institutions”, Ministry of Finance, New Delhi. Return to Text. 8. Concerns have been raised over the recent amendments made in 2020 to the Banking Regulation Act, 1949 about the possibility of RBI’s role undermining the autonomy of states with regards to cooperative banks. Return to Text. 9. Government of India . 2020 . “Annual Report: 2019-20”, Department of Agriculture, Co-operation, Farmers’ Welfare, Ministry of Agriculture and Farmers Welfare, New Delhi. Return to Text. 10. Supra Note No 6. Return to Text. 11. Dwivedi, R.C. 1989 . “Jawaharlal Nehru: His Vision of Cooperatives”, The Co-op Times, New Delhi. Return to Text. 12. Government of India . 2009 . “Report of the High Powered Committee on Cooperatives”, Ministry of Agriculture, New Delhi. Return to Text. 13. Jain, L.C. and K. Coelho.1996 . “In the wake of Freedom: India’s Tryst with Cooperatives”, Concept Publishing Company, New Delhi. Return to Text. 14. Baviskar, B. S. and D.W Attwood. 1991 . “Fertile Grounds: Why do Cooperatives Flourish in Western India?”, IASSI Quarterly 9, no. 4: 82–99. Return to Text. 15. As quoted in “ Co-operative Societies In India (undated) “ p.176. [http://lib.unipune.ac.in:8080/xmlui/bitstream/handle/123456789/2745/10_chapter%204.pdf?sequence=10&isAllowed=y]. Last accessed on July 28, 2021. Return to Text. 16. Supra Note No 7. Return to Text. 17. Supra Note No 15, pp. 164-65. Return to Text. 18. Agarwal, B. 2010 . “ Rethinking Agricultural Production Collectivities “, Economic and Political Weekly, Vol. 45, Issue. 9, pp. 64–78, February 27. [https://www.epw.in/journal/2010/09/special-articles/rethinking-agricultural-production-collectivities.html]. Return to Text. 19. As per available information there were 67,755 mutually aided cooperative societies, 7374 producers’ companies, and 1277 multi-state cooperatives. Return to Text. 20. Supra Note No 1, p.6. Return to Text. 21. Supra Note No 12. Return to Text. 22. Mishra, P. 2021. “ Change of Law: Plans to bring co-ops under Concurrent List “, Financial Express , July 22. [https://www.financialexpress.com/economy/change-of-law-plans-to-bring-co-ops-under-concurrent-list/2295153/]. Last accessed on July 28. Return to Text. 23. Attwood, D. W. and Baviskar B. S . 1988 . “Who shares? Cooperatives and Rural Development”, Oxford University Press , New Delhi. Return to Text. 24. Shah, T. 1996 . “Catalysing Co-operation: Design of Self-Governing Organisations”, Sage Publications , New Delhi. Return to Text. 25. For example, the share of Credit Cooperatives has declined from 62% in 1992-93 to 13.4 % 2016-17. Return to Text. 26. Dave Grace & Associates. 2014 . “ Measuring the Size and Scope of the Cooperative Economy: Results of the 2014 Global Census on Co-operatives “, April. [ https://www.un.org/esa/socdev/documents/2014/coopsegm/grace.pdf]. Last accessed on July 23, 2021. Return to Text. 27. NITI Aayog . 2017 . “India: Three Year Action Agenda,2017-18-2019-20”, NITI Aayog, New Delhi. Return to Text. 28. NITI Aayog. 2018 . “Strategy for New India@75”, NITI Aayog, New Delhi. Return to Text. 29. Ray, S. 2021 . “ Birth of an Alternative Development Paradigm: Unfolding of Transformative Mode of Production “, ICAS:MP Occasional Paper Series-1. [https://micasmp.hypotheses.org/occasional-paper-1]. Last accessed on June 25, 2021. Return to Text. 30. Nash, J. et al. (ed). 1976 . “Popular Participation in Social Change: Cooperatives, Collectives and Nationalised Industry”, Mouton Publisher, The Hague. Return to Text. 31. Roy, E.P. 1981 . “Cooperatives: Development, Principles and Management”, The Interstate Printer & Publishers, Danville. Return to Text. 32. Shylendra, H.S. 2013 . “Microfinance and Cooperatives in India: Can the poor gain from their coming together?” International Journal of Rural Management , Vol. 9, Issue. 2, pp.151-181. Return to Text.

One of the consequences of the COVID-19 pandemic is the change in the way in which societies - individuals and groups, businesses and governments - op

Migration from India’s villages is linked to poverty, the lack of livelihood opportunities and, in some States, feudal structures that dominate rural societies. COVID-19 and the lockdown implemented on March 24, 2020, to contain the spread of the pandemic resulted in traumatic conditions for migrant workers stranded across India. Bihar is second only to Uttar Pradesh in the number of out-migrants. In this Policy Watch, Girija Shankar and Rakhi Kumari discuss the impact of the COVID-19 lockdown in Baisi, a block (sub-district) in Bihar, from where workers move to 17 States and Nepal as short-term migrants. In an exploratory study conducted in April 2020, they find that the lockdown resulted in drastic changes in villages: the rural economy was disrupted, spending priorities had changed, and savings and investments fell. Interventions by the Union and State governments appeared to have a minimal effect on boosting demand and providing sustainable income support opportunities. CONTENTS I. INTRODUCTION II. THE MIGRANTS FROM BAISI III. THE DISRUPTED MIGRANT ECONOMY IV. THE IMPACT OF THE PANDEMIC ON SPENDING PATTERNS V. REVIVING RURAL BIHAR – AN UPHILL TASK I. INTRODUCTION Bihar, with nearly three times the national population density and about a third of its urbanisation rate, has been a source State for internal migration for centuries. 1 It is India’s most densely populated State (1,102 persons/per square kilometre), compared with a national average of 382. 2 Moreover, with only 11.30 per cent if its population living in urban areas, it naturally follows that Bihar’s population is predominantly rural (88.70 per cent). The Bihar Economic Survey 2019-20, provides sectoral growth rates in GDP/GSDP 3 from 2013 to 2019. 4 Figure 1 shows the growth in GDP/GSDP in the secondary (manufacturing, EGWUS, 5 and construction) and tertiary sectors (transport, communications, and storage), and a sharp decline in the primary sector (agriculture and allied activities) in 2018-19. Picture1jpg Source : Bihar Economic Survey 2019-20. The State’s poor performance in development indicators has placed it in a cluster referred to as the BIMARU, 6 an acronym for Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh (U.P.). The State has high levels of poverty and illiteracy, a defunct health care system, and a corrupt political administration. However, the situation was not the same historically, as the region was the seat of empires in ancient India. There are several reasons behind the economic decline of Bihar from its ancient glory despite its rich alluvial river valley and generous natural resource endowment. Economic policies and the State’s decline One view on the economic deterioration in the modern period is that it began with the introduction of opium and indigo farming at the behest of the British in the 1920s, which took over almost entirely the land under sugarcane cultivation. Around the same time, the textile industry, which began in the early nineteenth century and sustained about 60,000 people in the region, was also on the decline 7 , 8 due to a combination of social, economic, and political factors. According to Rasul and Sharma, the process of marginalisation, which began during the colonial rule, was “further reinforced by the [Union] government’s policy of ‘freight equalization’, which nullified the comparative advantage of Bihar and U.P. in natural resources by subsidizing railway freights of industrial inputs like coal, iron ore, steel, cement, and other bulk resources…which undermined the State’s “capacity to invest in health, education, and other social and physical infrastructure, and resulted in low human development.” 9 Added to these factors is the reality that people employed in the agricultural sector had among the lowest wages across the country. Between 1987-88 and 1989-90, the average per capita income (at current prices) in the agriculture sector was ₹948, against the national average of ₹1,522. This deficit was primarily due to a severe lack of research facilities and technology support, and institutional backwardness. In 1989-90, the per capita net value added 10 in the manufacturing factory sector in Bihar was only ₹305, against the national average at ₹514. 11 Nevertheless, in recent years, the Bihar government has claimed that the poverty ratio has reduced compared with previous years. 12 Migration, an escape from economic and social subjugation A historical trait that has dotted Bihar’s socio-economic landscape is out-migration. As per the estimate of the Economic Survey of India 2017 , inter-State migration in India was close to nine million between 2011 and 2016, with the highest number of migrants hailing from U.P. and Bihar, followed by Madhya Pradesh, Punjab, Rajasthan, Uttarakhand, Jammu and Kashmir, and West Bengal. 13 Migration from Bihar can be traced back to the 1830s when people were moved as indentured labourers to the British colonies of Mauritius, Guyana, Trinidad, and Fiji. In the 1960s during the spread of the Green Revolution, migration began to Calcutta (now Kolkata), the capital of West Bengal, and in the 1990s and the 2000s, people started moving across the country. 14 This phenomenon of outward migration from Bihar is intricately linked to poverty, the lack of livelihood opportunities, and the prevalence of feudalism in the agriculture sector. In Migration and livelihood in historical perspective: A case study of Bihar, India, Arjan de Haan 15 discussed a unique pattern of migration that existed for 100 years, where the work offered was relatively permanent in nature. Unskilled labourers migrated to the industries in Kolkata while their roots remained in the villages of their origin. Their savings were first spent on the basic needs of the family and then on asset creation, like buying agricultural land. 16 In his speech at the United Nations General Assembly in 2006 on international migration, the then Secretary-General, Kofi Annan, pointed out that “Migration is a courageous expression of an individual’s will to overcome adversity and live a better life”. 17 Mobility is the inherent characteristic of an individual. As the World Migration Report 2020, highlights, it “appears to be closely linked with the level of development in each country, which, in turn, is linked with the distribution of the population in each country”. 18 It is the result of the individual’s endeavour towards a social, political, spiritual, economic, and environmental balance. However, the proximate reasons for migration have always changed with time and space. Figure 2 shows the change in the reasons and destinations for migration over the period of a decade. Picture2jpg Source : Report of the Working Group on Migration, Govt. of India, 2017. 19 Migration and the migrants have always been a serious branch of inquiry among researchers and have fascinated policymakers. Development expert de Haan, in his work on migration 20 in Bihar, focused on “how migration has been caused by and in turn influences poverty and livelihoods for men and women”. Dutta and Mishra focused on the impact of male migration on the lives of the women in Bihar. 21 They pointed out that male migration functioned as the catalyst for enhancing women’s mobility, even as their burden of work increased in agriculture. Although most women remained in jobs that conformed to their traditional roles; in some communities, the women switched over to other occupations. In terms of changes in the pattern of household behaviour, the decision on spending of money was taken by the women even in castes placed lower in the social hierarchy. The Government of India sees migration as an opportunity. Its Report of the Working Group on Migration highlights the view that migrants “fuel the Indian economy by carrying human capital to regions where it is needed, and enabling the acquisition of new skills and a better standard of living”. 22 Definitional framework of migrants in India Studies on migration in India are shaped by official definitions. In addition to migration figures based on place of birth and duration of migration, data are also available on migration by place of last residence, which are more accurate in analysing current migration. According to the Census of India 2001’s Data Highlights - Migration Tables, 23 “A person is considered as migrant by place of birth if the place in which he is enumerated during the census is other than his place of birth. As a person could have migrated a number of times during his lifetime, migration by place of birth would not give a correct picture of the migration taking place currently. A person, on the other hand, is considered as migrant by place of last residence, if the place in which he is enumerated during the census is other than his place of immediate last residence. By capturing the latest of the migrations in cases where persons have migrated more than once, this concept would give a better picture of current migration scenario.” The National Sample Survey Organisation (NSSO), in its 64 th survey, 24 defines migration and migrants 25 as follows: Those movements which resulted in change of the usual place of residence (UPR) 26 of the individuals were treated as migration and a household member whose last usual place of residence was different from the present place of enumeration was considered a migrant. [Emphasis added]. Return to Contents II. THE MIGRANTS FROM BAISI India’s internal migration numbers (from rural to other rural areas and urban areas) stood at 73.8 million during the decade ending 2001. 27 The COVID-19 pandemic has rendered India’s migrant workforce vulnerable, especially those working in the informal sector. In addition to comprehensive government support in health, cash transfer, and other social programmes, these migrants need protection from discrimination. 28 The plight of the migrant workers after the lockdown was imposed was traumatic: images and videos of the multitude treading the roads on foot or by any other means—children in tow, carrying whatever they considered valuable—to make their way home stirred the soul of the nation. The workers, who were termed the “fuel of the Indian economy”, were suddenly considered liabilities. The Union and State governments, as was required of them, did put in place some relief measures 29 but they were clearly overwhelmed by the sheer magnitude and suddenness of the reverse migration. Soon, the need to recount the figures of the migrants became an urgent requirement, exposing the manner in which the Inter-State Migrant Workmen Act, 1979, had been given the go-by in the past. As opinion-writers had correctly pointed out: “In the immediate aftermath of the lockdown, state governments were taken unawares by inter-state migrants who were desperate to return home. Many had lost jobs, would not be able to afford rent and were afraid of falling seriously ill away from their families. The full and proper implementation of this law would have meant that state governments had complete details of inter-state migrant workmen coming through contractors within their states. While this would still leave out migrants who move across states on their own, a large segment would be automatically registered due to the requirements of the Act. States would consequently have been better prepared to take steps to protect such workmen during this lockdown. However, almost no state seems to have implemented this law in letter and spirit.” 30 Decades of indifference to this important legislation to safeguard migrant labourers was evident when Governments were unable to provide even estimates, thereby affecting relief work. 31 Baisi’s migrants – patterns and reasons Baisi block in Bihar’s north-eastern Purnia 32 district is a remote block with 45,092 households and a population of 2,27,706. Illiteracy is acute, with only 73,825 persons registered as literate (32.42 per cent). 33 A majority of its population are Muslims and most of them are migrant workers. 34 The Mahananda River that flows through the block, floods its plains almost every monsoon leaving behind very fertile soil. A major chunk of the population are “non-workers”, who, in all probability, migrate mainly to Gujarat, Maharashtra, Rajasthan, Delhi, U.P., and Haryana. Some migration to 17 other States and Nepal also takes place. Picture3jpg Source : Government of Bihar [ https://purnea.nic.in/about-district/map-of-district/ ] The weighted mean of the distance travelled by the outward migrants from Baisi block is 1,727.23 km. The sector in which they find employment determines the duration of migration. Agricultural labourers migrate for 45 days-60 days in a year during the sowing and harvesting seasons; in the construction sector, migration is for 6 months-8 months depending upon the contractors and the contract; and in tailoring it is for 8 months-10 months. If migration from the villages is for a short period of time, it is either circular migration 35 or seasonal migration 36 (as in the case of agriculture). Although migration theories view such movement of the workforce simply as consequence of economic development, 37 reasons for migration may vary depending on the socio-economic condition of the individuals. For some it could be for medical purposes, marriage, or to earn money to repay loans, while for others it could be to shore up savings to construct a house, or for other forms of asset creation. Higher wages and easy availability of work are, therefore, also factors that attract migrants to venture out of the comfort of their villages/towns. Migrant workers in Bihar generally move in groups and follow familiar patterns. Workers from a particular village/town migrate to the same State and take up the same occupation (Table 2.); they sometimes find employment in the same company that is referred to them either by their family members or by the contractor. Migration to the same profession from the same village depends on the “caste structure” of that village. For example, members of the Sharma 38 community in Chopara often find employment as carpenters in Gujarat. The highest number of migrant workers engaged in carpentry is from the Chopara Panchayat, in tailoring from Minapur, and in construction from Bangaon (Table 1). Table 1: Profession and Panchayat-wise Percentage of Migrants Migrated From Agricultural worker Carpenter Construction Tailoring ASJA MAWAIA11.573.812.105.61 BANGAON0.523.9315.876.50 CHIRAIA12.1011.4511.467.98 CHOPARA12.6313.603.982.90 GANGHAR0.006.202.577.78 MALHARYA3.158.234.749.16 MINAPUR27.893.6915.7319.36 PURANAGANJ1.0513.249.5610.44 SADIPUR BHATHA3.1510.149.093.54 SIRIPUR MALLAHTOLI0.007.152.17.04 Other Panchayats27.9418.5622.8019.69 Grand Total 100.00 100.00 100.00 100.00 Source : Primary data collected by authors from migrant workers in quarantine. Although a majority of the migrants are employed in tailoring, construction, and carpentry, others take up different trades. Table 2 presents the professions generally taken up by migrants from the Baisi block. Table 2: Occupations of migrant workers from Baisi Block Migrant Occupation Number of Migrants Percentage Agricultural worker1903.83 Carpenter83816.85 Construction1,47429.63 Cook360.72 Driver80.16 Electrician90.18 House Keeping30.06 Marketing60.12 Mechanic100.20 Other711.43 Retail Sector140.28 Tailoring2,02940.79 Teacher10.02 Technician2855.73 Grand Total 4,974 100.00 Source : Official records maintained for the quarantine of the migrant workers. A major chunk of this migrant workforce is employed in tailoring (40.79 per cent), followed by construction (29.63 per cent) and carpentry (16.85 per cent). Migration begins at a very young age for the residents of Baisi; the youngest among the migrants were found to be 10-year-olds who migrated to Delhi and Rajasthan to work in the construction sector and/or tailoring units. Mohamed Afraz of Harintor Panchayat, a village of 784 houses and a population of 3,867, 39 migrated with his maternal uncle to Rajasthan to be employed in a sports tailoring unit when he was 14 years old. Initially, he worked with his maternal uncle and gradually acquired the skills required to move into the job market. Now he is 22 years old and stitches 8-10 pieces of sports material a day. He is paid on a piece rate basis and ends up earning, on an average, ₹15,000 to ₹20,000 per month. 40 He and his five brothers own less than half-an-acre of agricultural land in which he has a small share. The land is looked after by his elder brother. Mohamed got married at the age of 20 years and now his responsibility towards his family has increased. The story is similar for almost all labourers in the tailoring sector who migrated when they were very young. Initially, they spent time picking up skills and later started working, often with the same employer but on a higher wage. Most of them are either landless or have a paltry share of land. The needs of the family dictate the duration of migration. 41 The maximum numbers of outward migration came from those in the 20-29 years age group, followed by those in the 30-39 years age group. Table 3: Age Group Distribution of the Migrants Age Group Number of Migrant Percentage 10-1967013.47 20-292,33446.92 30-391,23224.77 40-4951610.37 50-591883.79 60-69320.64 70-7920.04 Grand Total 4,974 100.00 Source : Official records maintained for the quarantine of the migrant workers. As Table 3 shows, 46.92 per cent of the migrant workers are in the age group of 20-29 years. With an increase in age, there is a decrease in the percentage of migrants as the responsibility of earning is passed on to the younger generation and the elders remain at home and take care of the family. Amar Kumar Yadav, who used to migrate to Punjab for agricultural work, is now a farm hand in his village. He is 31 years old and lives with his family. For the past two agricultural seasons, he did not migrate for work in Punjab but lives in the village and takes care of his family. 42 It is now the turn of his younger brother, aged 24 years, who migrated to Pune this March as a contract worker in a construction firm. His earnings will enable him to contribute to the construction of his family house, which is in progress in Baisi. He plans to get married soon and it is his responsibility to provide financial support, as he will require a separate room after his marriage. If seasons, availability of food, and reproductive cycles determine the migratory patterns of birds, agricultural seasons and festivals are the deciding factors for Bihar’s agricultural workers. Normally, a labourer migrates for 9 or 10 months for work and spends 2 or 3 months at home. Generally, the migrants return home at the end of April when the harvesting of maize is at its peak and for the Ramadan celebrations. A migrant, Sahanawaz, returns home in mid-April every year to look after the harvesting needs at his small landholding and returns to his workplace after celebrating Ramadan with his family. Table 4: Baisi’s Migrants and the Agriculture/Festival Calendar January February March Sowing of Garma rice after harvesting of mustardMigrants at work Migrants at work Harvesting of maize starts at the end of the monthMigrants at work April May June Harvesting of maize, solarisation, and sellingStart of the month of RamadanMigrants start returning Ramadan and EidHarvesting of Garma riceReturn of migrants continues Start of monsoon and sowing of riceMigrants stay at home July August September Monsoon and floodsMigrants stay at home End of monsoon and floodsTransfer of flood relief amount (₹6000 per HH)BakridMigrants stay at home Transfer of agriculture loss compensationMigration resumes / begins October November December Sowing of maize (early variety) and mustardSome migrants migrate after the sowing of maize.Migrants at work Sowing of maize (late variety)Migrants at work Migrants at work Source : Based on the authors’ observations for two years. Return to Contents III. THE DISRUPTED MIGRANT ECONOMY What is the purpose of migration? Deshingkar et al., 43 attempt to derive the quantum of remittances using Money Orders sent from different States to Bihar. However, there are various other methods to transfer money, which has become easier over the years. After the implementation of the Pradhan Mantri Jan Dhan Yojana, many villagers have bank accounts. 44 A migrant now remits his savings either to his own account or to his wife’s account, albeit with caveats on spending. In Baisi, migrants generally use more than 50 per cent of their savings to either repay loans or redeem mortgaged jewellery; the rest is spent on agriculture, festivals, marriages, medical exigencies, or for establishing a small business. Migration had offered them good returns, enabling them to afford a few non-essentials after fulfilling their needs. The pandemic, however, resulted in several disruptions for the migrant economy. Changing priorities for borrowing Vishal, a moneylender in the Baisi local market, says that during this pandemic, loan disbursal had increased compared with previous years. Many women mortgaged their jewellery for petty loans. Often, such loans were to purchase rations, start a small business, or to meet medical expenses. Why would the women not sell their jewellery to derive the maximum value? They generally mortgaged their jewellery instead of selling them because someone from the family would migrate for jobs and soon be able to repay the loan and repossess the pawned jewellery. Although this is a common trend in Baisi, the lockdown changed things around. There are several loans that are not repaid, he said. “In February, I was afraid seeing the falling value of gold. If it continues, I am going to run into a big loss. Migrants are the major investors in the local markets.” 45 A vendor at a textile shop said that his annual income depended on the festival and marriage seasons (October to June). This year, the entire month of Ramadan was under lockdown. Although he could not estimate the decline in the number of customers, he is certain that his monthly income fell by 75 per cent. There was hardly any supply of new clothes and footfalls were also decreasing.The individual’s capacity to invest in the market reduced, consumption priorities changed, and people started buying groceries at higher market prices. The workers who lost their jobs and returned home due to the lockdown met the expenditures from their savings while waiting for the lockdown to end, so that they could return to work. Not surprisingly, by the end of April, buses from States like Punjab, Haryana, and Rajasthan were seen in the villages of Baisi Block to ferry back the migrant workers. Bihar is a predominantly maize-growing State, contributing 8.9 per cent of India’s total maize production. 46 It is a cash crop that requires high investments. Although many migrants do not own much agricultural land, some of them invest in maize cultivation or extend loans to family members. With the imposition of a nation-wide lockdown between March 24, 2020 and May 17, 2020, all shops were ordered to be shut down and only emergency services such as medical stores and ration shops were permitted to function. In Baisi, however, the lockdown was followed more in the breach. Barely a week into the lockdown, textile shops were functioning surreptitiously, vegetable vendors were back on the roads, mobile shops up and about, barber shops open, and many other activities going on. Farmers, for their part, waited for middlemen to sell harvested maize but disappointment was in store, as this year’s price of maize was at least ₹500 lower per quintal than the previous year. 47 Market prices of vegetables, however, remained constant or fell only marginally as locally grown vegetables were in abundance. This, in turn, affected the vegetable-growing farmers as they were paid less for their produce. The opportunity to market agricultural produce was lost due to breakdown in the supply chain during the lockdown. Loss of incomes resulted in drastic reductions in consumer spending. In addition to decreased remittances from the migrants, their investment in the rural economy fell. The economic consequences of the pandemic have, therefore, been adverse for Baisi’s rural economy on all fronts: income, expenditure, savings, and investment. Return to Contents IV. THE IMPACT OF THE PANDEMIC ON SPENDING PATTERNS The pandemic and the subsequent lockdown brought into sharp focus issues concerning public provisioning of food and access to government services. Bharat Yadav, a 45-year-old construction worker, has been working for the past seven months in a private construction firm in Purnia. He said the situation in Purnia city, where all shops were shut and there was no movement of people, was far different from what prevailed in the villages. He receives his monthly salary (₹12,000) either on a weekly or monthly basis. Construction work, however, stopped after the lockdown. There are six members in his family. He has access to the Public Distribution System (PDS) and there is no problem in accessing the ration shop, but he now has to purchase more than what is provided through the PDS, which includes 5 kg of rice, 3 kg of wheat flour, 4 kg potatoes, and 2 kg pulses.This exploratory study in Baisi, conducted during the month of April, finds that soon after the enforcement of the lockdown, the basic need for people was food and medicine. In many cases, only a single member in the family had access to the PDS, which was not sufficient for the rest of the family members. The required rations had to be purchased from the nearest PDS outlet, and some households were left with rations that lasted merely 4 or 5 days. Soon, the price of groceries started increasing in the market. Though the administration did try to put a check on such malpractices, it could not be enforced beyond a point. Supply was limited and people had little choice but to buy the commodities at a higher price. To meet such expenses, they began borrowing money from easily accessible informal sources, for instance relatives.Once support from relatives dried up, they had to fall back on moneylenders. Those who had jewellery for mortgage could borrow at 4 per cent interest but others, without collateral, had to pay anywhere between 6 per cent and 10 per cent. A customary practice in Baisi block is that the women generally borrowed money by mortgaging their jewellery. They get an amount equivalent to half the current value of the jewellery. In an interview, a local moneylender said during the lockdown people borrowed extensively to purchase rations and migrants often took loans to meet their daily expenses.Meanwhile, the Government of Bihar provided some welfare measures: offering free ration for a month to all ration cardholders, a one-time cash transfer of ₹1,000 to ration cardholders, payment of pension for three months in advance to all pensioners, including old age pensioners, widows, and the physically challenged, and releasing pending scholarships to all students (Surya, 2020). The monetary benefits were deposited directly into the beneficiary’s account. Once the cash transfers were made, people began thronging banks in the hope of withdrawing the sum to buy essentials. Lockdown restrictions, however, ensured that their access to money in the bank was severely curtailed. Bihar holds the dubious distinction of having the highest number of people excluded from the National Food Security Act (NFSA): almost 14 lakh people in the State do not have a ration card. 48 Administrative lapses coupled with the indifferent attitude of officials and political corruption relegated these people to a state of exclusion. Recognising the need to act in a hurry, the State government took some steps to issue new ration cards during the pandemic. It was, however, too little too late. The inability of migrants to return to their villages in the early days of the lockdown resulted in a new difficulty to their families. Across Bihar, it is almost always men who visit government offices for any official work that needs to be done. Even before the lockdown, interactions with families of migrant labourers revealed that women knew little about government procedures and documents. In the absence of the men who could not return to their villages, this responsibility of interacting with government officials fell on the women who had no exposure to the workings of officialdom. They were either guided from afar by their husbands or sought help from tola sevaks (volunteers who assist children with their education and prepare them for enrolment in mainstream school, provide basic literacy to women, and create awareness about social security and welfare schemes among them) or relied on touts who had to be paid for their services. The lockdown brought another additional burden for the women in Bihar. In families owning agricultural land, the men often returned from their places of employment to work in their fields during the Rabi crop harvest season or the Kharif crop sowing season (see Table 4). This year, the lockdown put paid to their plans. The responsibility of managing such farm-related operations also fell on the women who were already saddled with running their households under uncertain conditions. They had to either seek help from neighbours or spend money hiring farm labour for sowing/harvesting. Many of those interviewed said that they did not know where their husbands worked as it had never been important for them; some of them only knew the name of the State where their husbands had gone in search of employment. Return to Contents V. REVIVING RURAL BIHAR – AN UPHILL TASK The International Labour Organisation (ILO) in its latest 49 briefing note, COVID-19 and the World of Work, observed that [w]orking-hour losses are expected to remain high in the third quarter of 2020, at 12.1 per cent or 345 million full-time equivalent (FTE) jobs. Moreover, revised projections for the fourth quarter suggest a bleaker outlook than previously estimated. In the baseline scenario, working-hour losses in the final quarter of 2020 are expected to amount to 8.6 per cent, or 245 million FTE jobs. 50 However, developing economies were witnessing weaker economic growth even before the onset of COVID-19. In India, the real gross domestic product (GDP) had fallen over nine consecutive quarters (EPW, 2020). According to Dev and Sengupta, 51 industry’s contribution to GDP, which was normally in the range of 30 per cent, had shrunk by 0.58 per cent in the fourth quarter of 2019-20, unemployment reached a 45-year high, investments in the private sector decreased, and rural consumption was also on the decline due to the effect of demonetisation. The pandemic, which came at a time when the economy was already slowing down, aggravated the downslide and the prolonged lockdown severely affected the labour market in India through overnight loss of livelihood for many especially those in the informal sector. A nation-wide lockdown started on March 24, 2020, and continued until May 17, 2020, with conditional relaxations after April 20. Much research was conducted on the effectiveness of the lockdown; a group of scholars came together to study the policies of five State governments—Maharashtra, Delhi, Tamil Nadu, Gujarat, and Punjab—and observed that enforcement of lockdown was done in places where there was high incidence of symptomatic infection among the population. They felt that the governments should conduct more tests in those areas (Sardar, T., et al.). Soon after the lockdown was announced, all modes of transport were suspended, and migrant labourers were stranded at their places of employment with no work and meagre savings. As the number of cases began increasing, so did discrimination against the labourers, forcing the migrants to resort to desperate means to return home. The first COVID-19 positive case in Bihar was reported on March 21, 2020. With numbers rising, a central team visited the State. 52 The number of government hospitals, the numbers of beds, doctors, and nurses available became a matter of concern. This is not surprising given the record of the State Health Department’s utilisation of funds from the Centre and the State. On average, the State’s Health Department managed to utilise only 53.86 per cent of the funds made available to it from the State and central pool from the financial year 2012-13 (Annual Report, 2018-19). These data clearly point to the State’s inefficient absorption capacity and its failure to use the available funds to improve infrastructure and services. Against this backdrop, the imposition of the total lockdown by the government was perhaps a mistake. Instead, the government could have initially implemented a partial lockdown allowing the migrant workers from other States to return home. A total lockdown could have been enforced once the movement of the migrants had stopped or declined. A strict quarantine policy for the returning migrants could have eased the possible spread of the virus among the local population. Improper facilities at quarantine centres also resulted in truancy whereby migrants slipped out during the nights owing to lack of any basic facilities except “free food”. 53 Merely offering subsidies to increase purchasing capacity may not be enough, as was experienced during the Bengal famine in 1943. The then colonial government, faced with severe scarcity of food grains, had allowed grain markets to sell the available grains at cheap prices. But the absence of regulation resulted in spiralling prices , 54 which worsened the fallout of the famine. It may be argued that comparing a famine and a pandemic is like comparing apples and oranges. However, lessons can definitely be learnt from the past. The Bihar government had announced a one-time subsidy of ₹1,000 and additional rations for all ration cardholders but the large-scale exclusion from PDS facility resulted in these benefits not reaching the people. To overcome this failure, the government employed the services of self-help groups like Jeevika to identify families who were eligible for the subsidy but did not have ration cards. 55 Even after such an exercise, the number of deserving beneficiaries who would remain excluded is still anybody’s guess. Ideally, the State Government should have provided free rations to all residents for a brief period, as was done by the Governments of Kerala 56 and Tamil Nadu, 57 to name two, and supplemented this by creating livelihood opportunities to boost consumer demand. The State Government now faces an uphill task of reviving the rural economy. In Bihar, 92.8 per cent of the farmers are small and marginal, which is higher than the national average of 83.5 per cent. 58 The Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) fits into the scheme of things here quite well, satisfying both individual and societal needs and is the most easily available option before the government. Although the performance of the State Government in the implementation of the programme has not been very encouraging, (Chopra, 2016), the fact that it had enormous potential was not lost on them. The Jind district in Haryana had shown positive results with a 135 per cent increase in physical performance and 36 per cent compound annual growth in financial performance (Sharma & Didwania, 2013). Tragically, the Union government has reduced the total fund allocation under the MGNREGS by 13 per cent this year. 59 Revising budgetary allocations and establishing efficient monitoring mechanisms to oversee resource utilisation and implementation of ongoing schemes will help in boosting the rural economy in the short term, especially during unforeseen emergencies such as the COVID-19 pandemic. A series of corrective measures to address institutional weaknesses, if required through effective utilisation of community and local grass-roots institutions, can help in the long run to both upscale rural economies like Baisi and meet the challenges posed by sudden disruptions. Return to Contents [ Girija Shankar graduated in Agriculture Rural and Tribal Development from Ramakrishna Mission Vivekananda University in 2016 and joined the Tata Institute of Social Sciences for post-graduate degree in Development Policy Planning and Practices with Rural Planning as a Special interest. He did his field work in the villages of Jharkhand, Rajasthan, and Maharashtra and, as a part of his post-graduate curriculum, worked as a research assistant in a project titled “The emerging trend of formal to informal outsourcing – A study of textile industry in Maharashtra” funded by the Goa Institute of Management. He also interned with the Foundation for Ecological Security (FES) and is currently working with BRLPS (Bihar Rural Livelihood Promotion Society) as a YP-BPM (Young Professional, Block Project Manager). As a Public Policy Scholar at The Hindu Centre for Politics and Public Policy, Girija studied the working of Farmer Producer Companies in Osamanabad, Maharashtra. Read Policy Report, Farmer Producer Companies: Preliminary Studies on Efficiency and Equity from Maharashtra in January 2019. He can be contacted at [email protected] . Rakhi Kumari graduated in Economics from Tilka Manjhi Bhagalpur University in 2020, and is pursuing her Master’s degree in Public Administrations from Central University Jharkhand. She has conducted research on women’s participation in agriculture and is currently working on the research topic “Agricultural labour migration in Khagaria District, Bihar”. She can be contacted at [email protected] ]. References: Annual Report (2018-19) . State Health Society, Bihar. Bhattarai, M., Vishwanathan, P., Mishra, R. N., & Bantilan, C. (2018) . Employment Guarantee Programme and Dynamics of Rural Transformation in India Challenges and Opportunities. doi: https://doi.org/10.1007/978-981-10-6262-9 Chatterjee, K., Chatterjee, K., Kumar, A., & Shankar, S. (2020) . Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model. Medical Journal Armed Forces India 76 , 147-155. Chopra, D. (2016) . Political Commitment in India’s social policy implementation: shaping the performance of MGNREGA. School of Environment and Development. Effective States and Inclusive Development Research Centre (ESID). Sardar, T., Nadim, S. S., Rana, S., & Chattopadhyay, J. (2020) . Assessment of Lockdown Effect in Some States and overall India: A Predictive Mathematical Study on COVID-19 Outbreak. Chaos, Solution & Fractals . doi: https://doi.org/10.1016/j.chaos.2020.110078 Sharma, R., & Didwania, M. (2013) . Performance Analysis of MGNREGA: A case study of District Jind. Zenith International Journal of Business Economics & Management Research . Surya, S. (2020) . Government of Bihar’s Response to COVID-19 (till April 19, 2020). PRS Legislative Research. Endnote: [ All URLs are last accessed on December 10, 2020 ] 1. Although in the initial stages of outmigration, the region comprising present day Bihar (which was created in 1912) was a source for military recruits for the Mughals and the East India Company, after the Permanent Settlement Act of 1793, a mix of factors resulted in distress migration. ( Draft Policy Framework for Improving the Conditions of Labour Migrants from Bihar , Prepared by Aajeevika Bureau and TISS for the ILO-supported State Consultative Meeting on Labour Migration from Bihar, October 12, 2017.) [https://tiss.edu/uploads/files/Policy_Brief_-_State_Consultative_Meeting_on_Labour_Migration__from_Bihar.pdf]. Return To text. 2. Government of Bihar (n.d.) . Distribution of Population Decadal Growth Rate, Sex Ratio, Density and Literacy by State - 2011 . [https://state.bihar.gov.in/main/cache/1/Figures/Table-001.pdf]. Return to Text. 3. GDP/GSDP: Gross Domestic Product/Gross State Domestic Product is the standard measure of the value-added created through the production of goods and services in a country/State during a certain period. Return to Text. 4. Government of Bihar. 2020 . Bihar Economic Survey 2019-20 , Finance Department, p. 5. [http://finance.bih.nic.in/Reports/Economic-Survey-2020-EN.pdf]. Return to Text. 5. Electric, gas, water supply and other utility services. Return to Text. 6. BIMARU is a term coined by the demographer Ashish Bose in 1985 for the States of Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh “to pinpoint India’s demographic malady” when he was “asked to brief the then Prime Minister [Rajiv Gandhi] on India’s family planning programme.” (See: Ashish Bose, Beyond Population Projections: Growing North-South Disparity , Economic and Political Weekly, Vol. 42 No. 15. April 14-20, 2007. p. 1328.) In the Hindi dialect of eastern U.P., bimaru means ‘sick’ (or ‘sickly). (See: Ashish Bose, National Population Policy, 2000: Swaminathan to Shanmugam , Economic and Political Weekly , Vol. 35, No. 13 (Mar. 25-31, 2000), p. 1059.). Return to Text. 7. de Haan, A. 2002. Migration and Livelihood in Historical Perspective: A Case Study of Bihar; India, The Journal of Development Studies , pp. 115-142. Return to Text. 8. Datta, A., and Mishra, S. K. 2011 . Glimpses of women’s lives in rural Bihar: Impact of male migration, The Indian Journal of Labour Economics , Vol. 54. Return to Text. 9. Rasul, G., and Sharma, E. 2014: Understanding the poor economic performance of Bihar and Uttar Pradesh, India: a macro-perspective, Regional Studies, Regional Science , Vol. 1, No. 1, 221-239, DOI: 10.1080/21681376.2014.943804. Return to Text. 10. Net Value added: Net value added is the value of output less the value of both intermediate consumption and consumption of fixed capital. Return to Text. 11. Sharma, A. N. 1995 . Political Economy of Poverty in Bihar, Economic and Political Weekly , October 14, Vol. 30, No. 41-42, pp. 2587-2602. Return to Text. 12. Op. cit. Government of Bihar. (2020). Return to Text. 13. Sharma, K. 2017. India has 139 million internal migrants. They must not be forgotten , World Economic Forum , October 1. [https://www.weforum.org/agenda/2017/10/india-has-139-million-internal-migrants-we-must-not-forget-them/]. Return to Text. 14. Datta, A., and Mishra, S. K. 2011 . Glimpses of women’s lives in rural Bihar: Impact of male migration, The Indian Journal of Labour Economics , Vol. 54, p. 458. Return to Text. 15. Arjan de Haan is the director of IDRC’s Inclusive Economies Programme and a development expert who focuses on poverty and public policy. Return to Text. 16. Op. cit. Return to Text. 17. United Nations. 2006. The Secretary-General[‘s] Address to The High-Level Dialogue of the General Assembly on International Migration and Development , September 14, New York. [https://www.un.org/migration/sg-speech.html]. Return to Text. 18. International Organization for Migration (IOM). 2019. World Migration Report 2020 , UN, New York, p.5. [https://publications.iom.int/system/files/pdf/wmr_2020.pdf]. Return to Text. 19. Government of India. 2017. Report on the Working Group on Migration , Ministry of Housing and Urban Poverty Alleviation, January. [http://mohua.gov.in/upload/uploadfiles/files/1566.pdf]. Return to Text. 20. Op. Cit. Return to Text. 21. Op. Cit. Return to Text. 22. Government of India. 2017. p. 7. Return to Text. 23. Census of India. 2001. Data Highlights, Migration Tables , Government of India. [https://censusindia.gov.in/Data_Products/Data_Highlights/Data_Highlights_link/data_highlights_D1D2D3.pdf]. Return to Text. 24. National Sample Survey Office, 2010: Migration in India, 2007-2008, NSS 64th Round (July 2007-June 2008) , Ministry of Statistics and Programme Implementation, Government of India, June. [http://mospi.nic.in/sites/default/files/publication_reports/533_final.pdf]. Return to Text. 25. The NSSO’s 64 th Round surveyed households across India on employment-unemployment and migration, enumerating people who migrated to the place of enumeration during the past 365 days. Return to Text. 26. Ibid : Footnote 1 “A household member whose last usual place of residence (UPR) was different from the present place of enumeration was considered as a migrant member in a household. In this survey, usual place of residence (UPR) of a person was defined as a place (village/town) where the person had stayed continuously for a period of six months or more.” p. H-i Return to Text. 27. Op. cit. Census of India, 2001. Return to Text. 28. World Bank. 2020 . COVID-19 Crisis Through a Migration Lens, Migration and Development Brief no. 32 , World Bank, Washington, DC, April. [https://openknowledge.worldbank.org/bitstream/handle/10986/33634/COVID-19-Crisis-Through-a-Migration-Lens.pdf?sequence=5&isAllowed=y]. Return to Text. 29. The Economic Times . 2020 . More than 21,000 camps set up for over 6,60,000 migrants: State governments , April 1. [https://economictimes.indiatimes.com/news/politics-and-nation/more-than-21000-camps-set-up-for-over-660000-migrants-state-governments/articleshow/74920798.cms]. Return to Text. 30. Krishnan., et al. 2020. Migrant Workmen Act, 1979, must be rationalised to remove requirements that disincentivise formalisation , The Indian Express , May 9. [https://indianexpress.com/article/opinion/columns/india-lockdown-inter-state-migrant-workmen-act-6400710/]. Return to Text. 31. Raghu, C. 2020. Lack of identity of migrant workers , countercurrents.org , June 4. [https://countercurrents.org/2020/06/lack-of-identity-of-migrant-workers/]. Return to Text. 32. Purnia is also spelt as Purnea. The Census of India uses the former spelling, and the Government of Bihar’s District website uses the latter. In this Policy Watch, the spellings in the Census of India are used for all place names. However, in the District Map, which is reproduced from the Government of Bihar’s website, the spelling used on the website is retained. Return to Text. 33. Directorate of Census Operations, Bihar. 2014. Census of India, 2011 – Bihar, Series-11, Part XII-B, District Census Handbook Purnia, Village and Town-wise Primary Census Abstract (PCA) . [https://www.censusindia.gov.in/2011census/dchb/1009_PART_B_DCHB_PURNIA.pdf]. Return to Text. 34. Deshingkar, P., et al. 2006 . The Role of Migration and Remittances in Promoting Livelihoods in Bihar , Overseas Development Institute, London. December. [https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/2354.pdf]. Return to Text. 35. Circular migration, also known as repeat migration, is temporary and usually repetitive movement of a migrant worker between home and host areas. For further reading on impact of lockdown on seasonal migrants, read Ravi Srivastava’s Understanding Circular Migration in India: Its Nature and Dimensions, the Crisis under Lockdown and the Response of the State (Institute for Human Development, WP 04/2020). [http://www.ihdindia.org/Working%20Ppaers/2020/IHD-CES_WP_04_2020.pdf]. Return to Text. 36. Seasonal migration is the movement of population from their place of origin for short periods depending on the sector in which they work as migrants. Return to Text. 37. de Haan, A. 2002. Op. cit. Return to Text. 38. The Sharma community is involved in carpentry in Bihar, and they are classified as an Other Backward Class. Return to Text. 39. Census 2011 . Harintor Population - Purnia, Bihar , Census Population 2020 Data. [https://www.census2011.co.in/data/village/223988-harintor-bihar.html]. Return to Text. 40. From an interview with the respondent. Return to Text. 41. The major reason for the migration is in search of livelihood opportunity, however, short-term migration is basically for the need of the family either for the medical purpose, marriage or for repaying debts. Return to Text. 42. From an interview with the respondent. The migrant starts as a second/additional earner in the family and then becomes the primary source of income. Return to Text. 43. Op. cit. Return to Text. 44. Under Pradhan Mantri Jan Dhan Yojana, total number of accounts in the rural/semi-urban areas is 31,396,414. [ https://pmjdy.gov.in/statewise-statistics ]. Return to Text. 45. In Baisi, women invest a large amount in purchasing jewellery if they have money in hand to spare. Return to Text. 46. Department of Agriculture, Cooperation and Farmers Welfare. (n.d.) . Farmer’s Portal – Maize , Ministry of Agriculture and Farmers Welfare, Government of India. [https://farmer.gov.in/m_cropstaticsmaize.aspx]. Return to Text. 47. In 2019 the price of maize was ₹1,700/- to ₹1,900/- per qtl and in 2020 it is ₹1,100/- to ₹1,200/- per qtl. Return to Text. 48. PTI. 2020. 14 lakh people in Bihar not getting benefits under food security act: Paswan , The Economic Times , April 23. [https://economictimes.indiatimes.com/news/politics-and-nation/14-lakh-people-in-bihar-not-getting-benefits-under-food-security-act-paswan/articleshow/75323510.cms]. Return to Text. 49. As on December 7, 2020. Return to Text. 50. International Labour Organization. 2020. ILO Monitor: COVID-19 and the World of Work, Sixth Edition, Updated estimates and analysis , September 23. [https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/documents/briefingnote/wcms_755910.pdf]. Return to Text. 51. Dev, M.S., and Sengupta, R. 2020. Covid-19: Impact on the Indian Economy , Indira Gandhi Institute for Development Research, Mumbai, April. [WP-2020-013.pdf (igidr.ac.in)]. Return to Text. 52. Tewary, A. 2020 . Coronavirus | Central team visits Bihar as COVID-19 cases rise , The Hindu , July 19. [https://www.thehindu.com/news/national/other-states/as-cases-surge-central-team-visits-bihar-to-assess-the-covid-19-situation-and-preparedness/article32130388.ece]. Return to Text. 53. Tewary, A. 2020 . Coronavirus | Migrant workers slip of out Bihar quarantine centres at night, return by day , The Hindu, April 8. [https://www.thehindu.com/news/national/coronavirus-lockdown-many-quarantined-bihar-villagers-missing-from-centres-at-night/article31291139.ece]. Return to Text. 54. Brennan, L. 1988. Government Famine Relief in Bengal, 1943, The Journal of Asian Studies , August, Vol. 47, No. 3, pp. 541-566. Return to Text. 55. Kumar, M. 2020. Bihar: Ration card-less families identified as eligible by as eligible by ‘Jeevika’ to be paid assistance of Rs 1,000, says CM , Times of India, April 21. [https://timesofindia.indiatimes.com/city/patna/bihar-ration-card-less-families-identified-as-eligible-by-jeevika-to-be-paid-assistance-of-rs-1000-says-cm/articleshow/75279178.cms]. Return to Text. 56. The Hindu. 2020. COVID-19 | Kerala to provide free ration to all . March 25. [https://www.thehindu.com/news/national/kerala/covid-19-kerala-to-provide-free-ration-to-all/article31160410.ece]. Return to Text. 57. PTI. 2020. Tamil Nadu to continue free Covid ration for family cardholders in June , The Economic Times, May 27. [https://economictimes.indiatimes.com/news/politics-and-nation/tamil-nadu-to-continue-free-covid-ration-for-family-cardholders-in-june/articleshow/76032890.cms]. Return to Text. 58. Behera, D., et al. 2013. Enhancing agricultural livelihoods through community institutions in Bihar, India (English) , South Asia rural livelihoods; Series 3 note no. Washington, D.C.: World Bank Group. April 1. [http://documents.worldbank.org/curated/en/467261468258525242/Enhancing-agricultural-livelihoods-through-community-institutions-in-Bihar-India]. Return to Text. 59. PTI. 2020. Budget 2020: MGNREGA funds down by 13%, marginal dip in other rural development schemes , The Economic Times, February 1. [https://economictimes.indiatimes.com/news/economy/policy/budget-2020-mgnrega-funds-down-by-13-marginal-dip-in-other-rural-development-schemes/articleshow/73847723.cms]. Return to Text. Related Resources COVID-19: Press Releases and Updates by the Government of India and WHO [HTML and PDF] . Source : Press Information Bureau, Government of India. Full Text: World Migration Report 2020 . Source : International Organization for Migration, November 2019. [https://publications.iom.int/system/files/pdf/wmr_2020.pdf]. World Bank Report: COVID-19 Crisis through a Migration Lens [PDF 1.69 MB] . Source: The World Bank Group (April 2020). [http://hdl.handle.net/10986/33634]. NSSO Data: Migration in India, 2007-2008 [PDF 4.5 MB] . Source : National Sample Survey Office Ministry of Statistics and Programme Implementation, Government of India (June 2010). Related Articles Chaturvedi, S. 2020 . Pandemic Exposes Weaknesses in India’s Disaster Management Responses , The Hindu Centre for Politics and Public Policy, September 3. Mudliar, P. 2020 . A Reality Check on India’s Search for Digital Utopia , The Hindu Centre for Politics and Public Policy, August 28. Ebenezer, R. 2020. Ensuring Zero Tolerance for all Forms of Forced Labour , The Hindu Centre for Politics and Public Policy, July 14. Ngullie, O. G. and Ansari, A. A. 2020 . India’s Public Distribution System and the Pandemic – Revisiting Delhi’s Beneficiaries , The Hindu Centre for Politics and Public Policy, June 26. Vijay, G. and Gudavarthy, A. 2020 . A Pandemic as a Political Reality Check , The Hindu Centre for Politics and Public Policy, April 15.

Never since the founding of the Indian republic have so many millions depended directly on India’s government machineries for sustenance. One reality that the COVID-19 pandemic has driven home is that the welfare state cannot be replaced and needs to be strengthened. In addition to market failures, the inability of markets to operate under extraordinary circumstances – such as the ongoing pandemic – places the onus on governments to emerge as providers of the last resort. In this interview-based empirical study, O. Grace Ngullie and Arib Ahmad Ansari, Independent Researchers, revisit beneficiaries who were respondents in a previous study by the first author on the Public Distribution System (PDS) in Delhi. (The names of all respondents have been changed to protect confidentiality.) While the earlier study focussed on the comparative benefits of cash transfers vis-à-vis provisioning of ration, the present exploratory study aims to find out the manner in which the PDS has worked for the poor in times of COVID-19 pandemic. This preliminary inquiry finds that the pre-existing problems with the PDS persist, thereby worsening the woes of the vulnerable who have been promised food security during the pandemic. For instance, there were differences reported in the quantity or rations received and promised, the quality of the food grains, exclusion, and access. The authors suggest a set of policy recommendations addressing each of the problems. The recommendations include utilising modern and emerging technologies to address supply chain issues, the creation of new cadre for monitoring, and upwardly revising the allocation. CONTENTS I. REVISITING DELHI’S PDS BENEFICIARIES II. QUANTITY, QUALITY, ACCESS – THE PROBLEMS PERSIST DURING THE PANDEMIC III. IMPACT OF THE PANDEMIC ON ACCESS TO FOOD IV. POLICY RECOMMENDATIONS V. CONCLUSION I. REVISITING DELHI’S PDS BENEFICIARIES The severe and unprecedented economic distress caused by the COVID-19 pandemic has made millions of people lose their livelihoods and become helpless making them rely increasingly – in some instances entirely – on government welfare schemes for their basic needs. The purpose of this exploratory empirical study is to assess the efficacy and the resilience of the Public Distribution System (PDS) in India as a provider of food security for the poor in times of debilitating emergencies of the nature of the COVID 19 pandemic. Though there has been plenty of good research 1 on the implementation of India’s PDS over the years with social scientists suggesting many relevant interventions, which facilitated gradual improvement in the overall strength of the PDS; none of these envisioned a time when the PDS would assume such a central role in the Indian state’s response to the extreme economic hardship brought about by this deadly pandemic. In times like these the market economy loses its automatic resource allocation ability and the responsibility of saving a sinking economy falls squarely on the state. Under such circumstances, the steps that governments take hold the only promise of hope for the struggling millions. This makes government initiatives the most crucial cogs in the overall response to a pandemic. The viability and the success of such programs depend on how aligned they are with the needs and the problems faced by the most vulnerable section of the population. Structure of the Delhi inquiry The importance of this study lies in getting first-hand evidence of the most acute problems faced by the people hit hardest by the pandemic – the poor who have lost their means of income because of either closure of workplaces, loss of jobs, or the inability to reach workplaces owing to the lockdown and need state support to live – through direct interaction with them. We begin with the principle that any initiative to alleviate the suffering of the poor has to primarily learn about the nature of their suffering. To this end, we ask how the PDS has worked during the time of the pandemic in providing relief to the vulnerable: where it is falling short, what are the aspects left unaddressed, where and to what extent PDS is misdirected, and so forth. Once we establish an understanding of the above, we aim to go forward to suggest ways, based on the information collected directly from the respondents, through which welfare policy measures such as the PDS can be made more effective and inclusive to help people tide over the periods of crisis.Accordingly, this empirical inquiry was structured under four themes. First, we tested people’s awareness about the government announcement on the increase of food grains allotment through the PDS due to the pandemic. The Government of Delhi, where this inquiry was conducted, announced a total of 7.5 kg food grains per person per month and the central government announced 10 kg of food grains per person per month. Second, we examined access to PDS during this pandemic. We verified the sought information on the food grains received by the respondents and identified problems faced by the people when accessing the PDS during this pandemic. Third, we assessed the impact of the PDS in reducing the hardship of the poor by examining the adequacy and quality of ration received by the beneficiaries in the context of attaining food security. Fourth, we studied the impact of the pandemic on livelihood and food access and explored government interventions that could alleviate the problems of job loss and food insecurity during this pandemic. Revisiting beneficiaries Constrained by the ongoing pandemic, which necessitated keeping a physical distance from respondents, we conducted telephonic interviews in June with PDS beneficiary households we came in contact with from a previous study (Ngullie 2017). These residents of households live in the districts of Northeast (Karawal Circle), Northwest (Kirari Circle), West (Vikaspuri Circle), and South West (Matiala Circle) in Delhi. The rationale for the selection of sites relied on the maximum number of PDS households in each district and circle. At the time of the sampling for the first study (in February 2015), Kirari had 44,449 PDS households, Karawal had 38,763 PDS households, Vikaspuri had 41,228 PDS households, and Matiala had 40,340 PDS households. At the time of the study, the list of households’ name with the house address was available at the website of the National Food Security, Delhi. To choose a sample of 40 PDS households, we adopted Systematic Random Sampling to make the survey evenly representative. For example, we divide the total number of beneficiaries in a Circle (say 1,000) by ten (to select 10 households from each Circle), which gives us 100. Subsequently, our target households would be 100 th , 200 th , 300 th and so on. This method enables us to make an unbiased selection from the entire list of beneficiaries. In case a particular beneficiary is not traceable or unavailable for some reason, the preceding beneficiary of the first selection is taken, that is, the 99 th if 100 th is not available, the 199 th if 200 th is absent, and so on. This method seeks to find the nearest possible alternative to the chosen beneficiary in case of her absence. We traced the households’ addresses, conducted the survey, and requested their phone numbers (with consent) for follow-up purposes. This time, out of 40 households contacted, 18 households, comprising 102 individuals, responded and enthusiastically consented to participate in the interview to study the working and the impact of the PDS in the current pandemic. Out of the 18 households, six are from the Scheduled Caste (SC) category, five are from the General category, three are from the Muslim community, two are Other Backward Caste (OBC-Hindu), and another two are OBC-Muslim. The respondents, who spoke on behalf of their households, comprised of 14 females and four males (husband or son) of the head of the household. The senior female in the family is the head in the ration card. Each interview lasted about 30 minutes. Return to Contents II. QUANTITY, QUALITY, ACCESS – THE PROBLEMS PERSIST DURING THE PANDEMIC We find it interesting that all the respondents were aware of the enhancement of food allocation owing to the lockdown under the PDS announced by both the State and the central governments. However, not all households received the same amount of food grains. Variations were reported in the quantity of food grains received from the PDS versus that which was announced. Out of 18 households, only eight households received the announced amount of 10 kg per person; eight households received 8 kg per person; one household received 5 kg per person; another household received only 4 kg per person for each month.For example, Sumitra, a resident in Kirari, North West Delhi received only 20 kg of ration for her four-member household at the rate of 5 kg per person. Gitanjali Devi and Vidhya Devi, residents in Karawal, North East Delhi received 8 kg of food grains per person per month for their family. As in normal, non-pandemic, times, the beneficiaries in Delhi received wheat and rice in the ratio of 4:1. For example, for a person receiving a total of 10 kg of food grains, the allocation would include 8 kg of wheat and 2 kg of rice, and for a person receiving 8 kg of food grains, it would be 6.4 kg of wheat and 1.6 kg of rice. As a special arrangement for the pandemic, the beneficiaries received special kits containing the following items: one litre of refined oil, a pair of soap, and a packet each of salt, sugar, chilli powder, and channa or chhole . Yet again, the distribution was not uniform as one-half of the respondents received it only once in the last two months and the other half received it twice. Exclusion – a major setback We found the exclusion of eligible members as a major setback in the PDS. Out of 102 individuals from 18 households, only 78 are registered in their respective family’s ration cards. For example, Naina Singh has eight members in her household but only five are listed in the ration card, which reduces the food entitlement for the family. Sangeeta Devi, an intermittent informal labourer is a sole breadwinner in a family of five, whose husband is bedridden due to a chronic illness she chose not to disclose, and who received a total of 24 kg of food grains for three members registered in the ration card. These cases reflect the extent of exclusion in the food distribution system. Denial of food entitlement to some eligible members not enlisted in the ration card was found to be pervasive. All the respondents have been struggling to register new members in the family’s ration card. With many citing bureaucratic hurdles, it indicates that government agencies are reluctant to update their ration cards. Whenever they approach the Fair Price Shops (FPS) or the rations office to register new members, they are either turned away or are asked to come at a later date making them give up the hope of getting it done. Eventually, they make peace with whatever reduced amount of ration they receive.In an exclusive case, a man used his Aadhaar card to collect his share of the ration after failing to add his name to the family’s ration card. Shalini Devi’s husband told her that he had filled up the ration card form and submitted it to the ‘government’ a ‘hundred times’ to get it updated; yet, it failed. Her husband managed to collect ration for the last two months based on his Aadhaar card. In this context, technological up-gradation embodied in the shift from ration card to Aadhaar card as the eligibility for receiving ration might work for the excluded individuals. On the other hand, several respondents informed about the low coverage of Aadhaar cards since not all family members possess one. For instance, only three out of five in a family or only five out of eight in another family possessed Aadhaar cards. Absence of behavioural norms at Fair Price Shops We find it alarming to learn that beneficiaries are troubled by the long queues and congestion at the Fair Price Shops in this time of the pandemic. Geetanjali Devi, a mother of three from Karawal, North West Delhi, was deeply concerned about the risks associated with the collection of rations in overcrowded spaces. Being a widow, she had no helping hand other than her children but she never allowed her children, despite their insistence, to collect ration. The problem of overcrowding was conspicuous and they evoked concern about the near-complete disregard for physical distancing norms. Though the beneficiaries expressed remarkable awareness of the protective measures to be undertaken during the COVID-19, they helplessly put themselves at risk because of the indispensable need for food. Respondent Shahana Khatoon reasoned that the constant increase in cases in Delhi might be due to people having to step out of their houses to fulfil their basic needs and hence, suggested the government deliver these basic needs at their doorstep. Inadequate quantity of disbursement Interrogating whether the ration from the PDS satiates the recipients’ needs for a month elicited the sharpest responses from the beneficiaries. While some responses expressed shock, some were clothed in amusement, and still, others bordered on anger upon an assumption that the entitled ration would ensure their basic monthly food needs. Najma Khatoon said “ Majak kar rahe ho kya?” (Are you joking?). Mahesh, son of beneficiary Prabhawati Devi retorted “ Aap khud sochiye, kaise poora hoga itna kam ration” (Please think for yourself how can such a meagre quantity suffice for the whole family). He illustrated that all his six family members physically labour throughout the day and their minimum wheat consumption is about 2.5 kg per day, amounting to 75 kg per month, whereas they receive only 8 kg per month per person amounting to only 48 kg per month from the PDS as the maximum amount. The beneficiaries admitted the benefit of doubling the ration in times of pandemic and expressed satisfaction and preferred frequent distribution of the kits, favouring such diversification of items that include cereals and other food essentials. With some members of the households excluded from the PDS, there was complete unanimity amongst the respondents on the need to increase the allocation of ration per household. The current food allocation lasts in the range of 12 to 15 days. The food grains and the free-of-cost kits during this pandemic has only given them temporary relief in an overarching climate of extreme hardship. Inconsistent quality The majority of the respondents reported that the quality of ration is inconsistent— sometimes it is fine, sometimes it is awful. Some expressed disappointments with the quality of wheat. Sugandha Devi explained, “ Bohot kharab gehu hai, roti kaari kaari banti hai aur swaad bhina hi hota” (the quality of the wheat is substandard; roti made from the wheat looks black and without taste). Another respondent, the son of beneficiary Nirmala Devi, reported that sometimes the packet of wheat contains a lot of thorns in it. The residue wheat after removing the thorns is a much-reduced quantity. The complaints were mainly of bad quality of wheat. Most of the respondents were satisfied with the quality of rice. Water woes and poor hygiene A pertinent issue that arose on the sidelines of our discussion over the telephonic interviews was the acute water crises across different locations in Delhi during this lockdown. Households residing in Kirari (North West) and Karawal (North East) in particular were the worst affected by the water crises. According to them, the water supply has been disrupted ever since the lockdown began and it only comes for half an hour in a day which is grossly inadequate. Water tankers came initially after complaints by residents but as the lockdown extended those tankers also stopped their service. Dhapar, a father of two, daily wage labourer and a resident of Kirari said, “ Ration chhod dijiye, paani ka samasya hai, jab paani hi nahi milega to jiyenge kaise” (Do not ask about ration, water is the main problem here: unless we get water how will we live). Asha Rani exclaimed, “How can the authorities expect us to follow the sanitization norms when we do not have enough water!” She indicated a lack of adequate water as a contributing factor behind the rise in cases. This particular issue we feel requires urgent remediation by government authorities if we are to get even close to our mitigation targets. Loss of livelihood due to lockdown All the respondent households suffered either a lay off from the employer or loss of income as a result of the pandemic. Out of 14 respondents who worked as labourers, seven did not get even a single day of work due to lockdown. The income of some respondents who were self-employed reduced to a negligible amount under the effect of the lockdown. Phoolwati’s husband narrated that they earn a livelihood by rearing buffalos and selling milk. However, for the last two months, buyers are unable to pay for the milk but are borrowing milk on credit and making promises to pay later when they regain their incomes. This has foreclosed any hope of income that they had from their animal rearing livelihood. This appears to be a representative case for many others who are self-employed, having exhausted their income owing to the macroeconomic shock that this pandemic has produced. Emphasising that a “labourer is the pillar of the economy; the government needs to take care of the labourer”, Priyank, a respondent, suggested that the government could provide employment assurance or subsistence allowance during such economic crises. He reflected that the government could have established manufacturing units for masks, sanitizers, protective equipment, and other such high demand medical equipment in rural areas to address the shortage of these essentials on one hand and employ rural residents on the other. Return to Contents III. IMPACT OF THE PANDEMIC ON ACCESS TO FOOD The loss of livelihood induced by the pandemic has severely hampered people’s access to food. Given the fact that massive unemployment and loss of livelihood has already engulfed the working millions due to the pandemic, and that some members of the households are excluded from the PDS, the quantity of ration provided by the government cannot act as a bulwark against hunger and want. It naturally leads us to the question of how they survive for the rest of the days without any source of income. Most of the respondents borrowed money to meet their food requirements. Thereafter consuming the ration from the PDS that lasts up to 15 days, they borrow money from their neighbours and friends. Similarly, those who received the kits only once in the last two months used their savings and borrowed money to buy these items again. Few are surviving on meagre savings while the rest are borrowing money from friends and neighbours. None of them could access bank credit due to lockdown. Each had developed their networks of informal borrowing, which they relied upon in times of extreme distress. In such a scenario, they expressed their anguish at falling deeper into a debt trap and not having a clue as to when they will be able to come out of it. The respondents declared that their meagre savings, ration from the PDS, and borrowed money from neighbours and friends are their only hopes of survival. The high share of food expenditure To fully understand the impact of the pandemic on economic access to food in Indian households, one has to consider the overall share of expenditure on food that Indian households incur on average. The average share of food in household total spending amounts to 43 per cent in urban India and rises to 53 per cent in rural India (NSSO 2011-2012: 106-107) 2 . For perspective, we can compare it to French households that spent only 13.2 per cent of their total expenditures on food and non-alcoholic beverages in 2017 (Eurostat 2018). These statistics while confirming Engel’s law— the poorer a household, the larger the share of total expenditures spent on food— also point to the uneven impact of economic hardship on access to food. The kind of economic shock generated by the COVID-19 might be the same for France and India, but its effect on the access to food is graver on the Indian population. Persistent problems aggravate suffering Our empirical studies prove that most of these problems have been occurring from way back (Ngullie 2017, 2018). Corruption, thus, has not been rooted out in Delhi, even though the Arvind Kejriwal government hiked the FPS dealers’ commission by 300 per cent in January 2018. The implementing machinery of the government has not yet established a proactive accountable system for the people. That many eligible individuals are excluded from the PDS has been enumerated time and again. Similarly, long wait and queue at the Fair Price Shops is a commonly reported problem. The lack of water and poor hygienic practices leading to food insecurity has been stressed many times. Moreover, the allocation norm of 5 kg of food grains per person per month under the National Food Security Act (NFSA) 2013 is grossly inadequate to meet basic monthly food needs. During this pandemic, PDS with enhanced ration has been a relief to the poor but with many shortcomings such as unequal distribution, exclusion, absence of social distancing norms at Fair Price Shops, and inadequate ration for the households alongside inconsistent quality. These problems have remained unaddressed for long. However, these lacunae in the PDS have never affected the vulnerable section so adversely as they do now. We have to examine these problems with one eye on the surrounding circumstances which have changed drastically for the worse in the wake of the pandemic. Earlier, even when the quantity was inadequate, distribution unequal, exclusion pervasive, quality inconsistent, people had other sources of income to supplement the ration they received under the PDS. One or two individuals from the household sending remittances from the city, income from various kinds of self-employment, and so on, provided succour to the poor in times of difficulty. Given the fact that all these sources have completely dried up, the situation is grim. Under such an overarching climate of hardship, we believe that any set of recommendations to be effective will have to speak to this new reality. Conscious of the above exigencies, we have attempted to make recommendations with a focus on the immediate measures that can be taken to reduce extreme hardship. Return to Contents IV. POLICY RECOMMENDATIONS We propose to make recommendations corresponding to the specific problems identified during the course of this exploratory empirical study. It is submitted that these suggestions are not exhaustive. Problem 1: Unequal/Uneven distribution For tackling the issue of unequal distribution we suggest taking the help of the new blockchain technology to reduce leakages and enhance transparency. The PDS involves a long chain of transactions right from the procurement of the food grains by the government agencies to the disbursement to the beneficiaries.The reasons for one household receiving 10 kg per person and another household in the same locality receiving 5 kg per person could go back to the PDS supply chain. The entire supply chain has various junctures, which are prone to manipulation leading to leakages, theft, and eventually culminating in the unequal distribution. Food grains are first procured by the government under the Minimum Support Price. Then, they go to millers identified by the government for hulling and are returned to the government. Next, food grains are moved to the State godowns from where they are further moved to the Block godowns within the State by selected transporters. Finally, from the Block godowns, food grains are sent to the Fair Price Shops for distribution. 3 This entire supply chain can be a part of blockchain using the distributed ledger technology. With the help of blockchain technology, every point where the product is moved and then stopped for collection or storage gets stored in the electronic ledger. This way the food grain can be tracked from the place where it is despatched to its destination. At present, we have the GPS tracking of trucks carrying PDS supplies from the FCI godowns. Installation of GPS was taken up for the first time in the 11 th Plan (2007-2012) on a pilot basis in Tamil Nadu and Chhattisgarh for tracking movement of vehicles transporting rations ( The Hindu Business Line , December 4, 2012). More recently, Delhi and Telangana Governments had issued directives that all trucks carrying ration items will have to have a GPS Tracking Device in them. Within Delhi, the Delhi State Civil Supply Corporation (DSCSC) had been entrusted with the installation of GPS trackers on trucks carrying rations ( The Hindu , July 29, 2015). While the GPS technology did help to an extent in preventing the diversion of grains in movement or during transportation, but it could not prevent the diversion of grains from the godowns or the FPS under the watch of officials. It is here that we could upgrade to blockchain technology. Given the Government of India’s emphasis on digitization and adoption of new technologies, there cannot be a better and a more opportune time to inaugurate the blockchain technology. However, as with every new technology, the full development of blockchain infrastructure might take time. Therefore we need some more immediate measures.One such mechanism for checking and making the process of distribution more accountable was suggested in mid-June by the Delhi High Court in a petition filed by Delhi Rozi Roti Adhikar Abhiyan which sought time-bound redress of complaints regarding non-supply of rations and transparency in the distribution of food grains. A Bench comprising Justice Hima Kohli and Justice Subramonium Prasad directed the Sub-Divisional Magistrates in every district to conduct a surprise visit at the FPS coming under their territorial jurisdiction and ensure proper functioning.We suggest that a separate cadre of government employees be established for this purpose and stationed at all the FPS. They could be called Ration Inspectors and their job would be to ensure impartial and hassle-free delivery of food grains from the FPS. The formation of such a cadre only needs a notification by the Ministry of Consumer Affairs, Food and Public Distribution, and the legislation can take place later. We do have a provision for periodic inspection of FPS by the Circle food supply officers and Special Commissioners as ordered by the Delhi government in response to numerous complaints received by the beneficiaries in 2015. Unfortunately, with no accountability and lack of supervision of these officers, inspections have been few and sporadic, and consequently, progress on the ground has been negligible. Therefore, having a cadre of officers permanently stationed at the FPS would have an impact.To ensure impartial discharge of duties by such ration inspectors, the existing Lokpal framework can be utilized. Any collusion or discrimination by the ration inspectors can be reported by any member of the public to the State Lokayukta who will initiate summary proceedings and adjudicate upon the guilt of the official. The period for disposing a complaint by the Lokayukta can be fixed at one month by making minor changes in the Delhi Lokayukta and Uplokayukta Act, 1995. Problem 2: Exclusion For including the excluded in the PDS during this pandemic, Abhijeet Banerjee, Amartya Sen, and Raghuram Rajan have gone on record recommending a temporary ration card for a period of six months to everyone who is in need with minimal checks. They have rightly remarked: “The cost of missing many of those who are in dire need vastly exceeds the social cost of letting in some who could perhaps do without it.” 4 We support this mechanism as it is an expedient remedy to counter an immediate situation. The Delhi government has initiated this type of temporary e-coupon system; this facility is available in Delhi government’s website, which allows an applicant to login with the mobile number providing details of family members and Aadhaar and generate e-coupon to collect ration from designated relief centres. We have not verified this initiative. For many years, many eminent scholars have been proposing universal food security legislation instead of a targeted one that excludes many deserving persons (see Swaminathan, M 2000; Sen, A 2009; Himanshu and Sen 2011; Ghosh 2010). Similarly, K.R. Venugopal, former Secretary to the Prime Minister 5 suggested that ration should be issued to every person even without a Ration Card or Aadhaar Card based on a spot summary enquiry. Such a method would enable government officials to know the beneficiaries while dispensing with the necessity of possessing an identity card. This will help the cause of their dignity as well. The emphasis should be on giving something to everyone who has come to collect ration throughout the period of lockdown. Doing away with the need of Ration Cards is particularly important in the current situation because of at least two facts: (i) lakhs of migrant workers stranded outside their home States do not have a ration card, (ii) lakhs of people who never applied and never possessed a food card have become needy due to the lockdown. A recent petition by the former Environment Minister Jairam Ramesh in the Supreme Court has argued for universal coverage of food security. They contended that despite the government’s move to double the entitlement under the PDS, a large number of people who do not have food cards or who do not have it at the time of need are being left out. The Supreme Court declined to pass any directions and instead directed the petitioners to first make a representation to the government. Interestingly, in a 2016 judgment in Swaraj Abhiyan v Union of India 6 , the Supreme Court had ordered all the State governments affected by drought to provide 5 kg of grains per person per month to everyone who wanted it including those who do not hold a ration card. State governments have not yet implemented this judgment in letter and spirit. Something along these lines needs to be done. This verdict should be deemed to include all State governments irrespective of their drought status and carried into effect without any further delay. The government officials would do well to remember the important principle given by the three stalwarts of economics – the cost of missing many of those who are in dire need vastly exceeds the social cost of letting in some who could perhaps do without it. The proposed One Nation One Ration Card scheme should become operational immediately. Had it been in place, much of the misery experienced by migrant workers, who found themselves ineligible to take rations in the States where they worked, could have been avoided. Problem 3: Absence of social distancing norms and congestion at the collection points Aiming to weed out corruption and diversion of food grains, and to attain transparency in service delivery, on March 6, 2018, the Aam Aadmi Party government in Delhi approved a proposal for doorstep or home delivery of ration to bring ‘maximum ease’ for the PDS beneficiaries 7 . Meanwhile, the central government’s stand on the doorstep delivery is contradictory; even as the central government supports the idea, the Lieutenant Governor (LG) rejected the Delhi government’s proposal. This power struggle between the central government and the State government was simplified by the Supreme Court ruling on Article 239AA of the constitution— that in the matters within the legislative competence of the State Legislature, that is, every matter except Police, Public Order and Land as provided under Art 239AA clause 3 the LG has to act on ‘aid and the advice’ of the elected government 8 Following the ruling, the Delhi government approved it again but it has not been implemented yet. In the context of the COVID-19 crisis, doorstep delivery of packaged ration might ease the problems of beneficiaries and prevent transmission of the disease. During this pandemic, all the respondents complained of overcrowding at the ration collection points. They also expressed fear of catching the disease due to the complete absence of social distancing norms, but still went ahead to collect the ration. This act of risking infection for food at FPS reflects the humanitarian crisis. Desperate queues and huge congestion for free ration have proven the indispensability of the PDS and the need to strengthen it especially in terms of ensuring coverage of eligible individuals while taking into account behavioural norms strategy such as doorstep delivery of ration in the context of this pandemic. If the doorstep delivery takes time to be rolled out, the government can consider increasing and diversifying distribution points. Government schools have already been used as PDS delivery points but other public spaces such as sports stadia, public parks, post offices can be roped in to distribute ration as an emergency measure. Problem 4: Loss of livelihood and Income We suggest the government should consider increasing both the coverage and the amount of cash transfers to all the vulnerable groups. 9 The Rs. 500 direct benefit transfer to the female accounts under the Pradhan Mantri Garib Kalyan Yojana which has been recently rolled out is grossly insufficient. The financial inclusion infrastructure put in place by the Jan Dhan Yojana can come handy at this time. The Union government can start with transferring either a one-time lump sum amount or smaller periodic amounts to all Jan Dhan Account holders. Thomas Reardon et al. have suggested cash for work schemes to employ workers to distribute emergency food rations, to upgrade sanitation in markets and other public spaces. 10 We support this suggestion. Problem 5: Inadequate Quantity If the problems listed under the heads of ‘Exclusion’ and ‘Unequal distribution’ are addressed, the core of the problem of inadequate quantity would be addressed. In a previous study in Delhi, on average, a person required 6.18 kg of wheat and 2.96 kg of rice per month (Ngullie 2017).In this connection, 10 kg of food grains consisting of wheat and rice are suitable, during all times, and not just due to COVID-19.Secondly, various State governments should consider establishing community kitchens providing free food as done by the Kerala government to cater to the hungry as an immediate measure. Kerala’s community kitchens have been quite successful in the current situation. Problem 6: Inconsistent quality On this issue, we think that technology-driven solutions have the potential to resolve immediate challenges as well as long term challenges. Use of upcoming technologies like Artificial Intelligence, Machine Learning, and the Internet of Things could be urgently adapted to eliminate the menace of adulteration and bad quality food grains. The monitoring of the quality of drinking water using machine learning has already been established by scientists. 11 Machine learning used in combination with sensor technology is used to measure the pH, colour, and turbidity of water and the result is recorded in a database. The system sends alert messages to the user whenever a recorded parameter is lower than the recorded values. Likewise, machine vision systems have shown to be effective in monitoring and evaluation of grain quality. 12 Such technologies should be promoted and employed as soon as possible for the purposes of monitoring PDS food grains. Return to Contents V. CONCLUSION An infectious respiratory disease, COVID-19, has again driven home the importance of well-designed and meticulously implemented food security policies that provide for timely access to adequate quality and quantity of food (and water), and good hygienic norms in times such as the ongoing pandemic.Most of the problems that India’s poor are encountering could be attributed to a lack of implementation of the existing food security framework, although the ‘law may look good on paper’ (Basu 2015). Barring a few recommendations like providing rations to needy people even without food cards and opening community kitchens, most other recommendations involve strengthening the existing PDS and other levers of food security.For instance, sections 14, 15, and 16 of the National Food Security Act (NFSA), 2013 mandate all State governments to set up grievance redress mechanisms and a State Food Commission to oversee the proper implementation of the law. However, States have not ensured such a mechanism to date. Some States have constituted their food commissions but they do not function fully. The NFSA also entitles persons who could not get their supply of food grains or meals to a food security allowance. It also entitles pregnant and lactating mothers to a maternity benefit of not less than Rs. 6,000 in addition to meals. If these provisions of the NFSA had been implemented, a lot of suffering could have been avoided. Return to Contents [ Dr. O. Grace Ngullie did her MPhil and Ph.D from the Centre for the Study of Law and Governance, Jawaharlal Nehru University, Delhi, under the supervision of Prof. Niraja Gopal Jayal. She is interested in the theoretical and empirical approaches to understanding the links between Politics, Governance, and Public Policy especially with problems related to Poverty, Inequality, and Gender issues. The policy interventions she has researched in depth are in the areas of Self-Help Groups, Public Distribution System, and Cash Transfers. She has worked as a Research Officer at the Indian Institute of Public Administration for the projects of Government of India on Concurrent Evaluation of Government Welfare Schemes. As a Public Policy Scholar at The Hindu Centre for Politics and Public Policy, Dr. Ngullie authored the Policy Report, The Politics and Governance of Social Policies in Delhi: Comparing Cash and In-kind Transfers in July 2018. Her recent work is on Gender Study in the Indian Administrative Service which she wrote for the Lal Bahadur Shastri National Academy of Administration. She can be contacted at [email protected] . Dr. Arib Ahmad Ansari completed his schooling from Cambrian Hall, Dehradun. He graduated with a Bachelor in Law at the Aligarh Muslim University. He worked as a practising lawyer in Delhi for some time but his interest in multidisciplinary research led him to pursue M.Phil and Ph.D from the Centre for the Study of Law and Governance, Jawaharlal Nehru University, Delhi. In his doctoral work, which he completed under the supervision of Prof. Niraja Gopal Jayal, he examined the ideas of nation and the judicial constructions of national identity in India, Pakistan, and Bangladesh. His Ph.D got awarded in 2018. He currently works as a freelance researcher. His areas of interest include Rights, Citizenship, Nationalism, International Law, Constitutional law, Law and Economics, and Politics of Recognition and Redistribution. He can be contacted at [email protected] ]. Endnote: [Note: A typographical error in Endnote 9 was corrected on June 27, 2020, in the HTML version.] 1. A collection of literature is available at the Right to Food Campaign ’s website. [http://www.righttofoodcampaign.in/food-pds/articles]. Last accessed June 26, 2020. Return To text. 2. A more recent household consumption survey was conducted in 2017-18 but the data has not been released yet. Return to Text. 3. Centre of Excellence in Blockchain Technology, National Informatics Centre, Ministry of Electronics and Information Technology . 2020 . Public Distribution System (PDS) . [https://blockchain.gov.in/pdspage.html]. Last accessed on June 25, 2020. Return to Text. 4. Sen, A, et al. 2020 . Huge numbers may be pushed into dire poverty or starvation…we need to secure them , The Indian Express , April 17. [https://indianexpress.com/article/opinion/coronavirus-india-lockdown-economy-amartya-sen-raghuram-rajan-abhijit-banerjee-6364521/]. Return to Text. 5. Venugopal K. R. 2020 . The Problem Of Plenty: Steps To Beat The Hunger Pandemic , Outlook Poshan , April 21. [https://poshan.outlookindia.com/story/the-problem-of-plenty-steps-to-beat-the-hunger-pandemic/351199]. Return to Text. 6. WRIT PETITION (C) NO. 857 OF 2015. Return to Text. 7. Aam Aadmi Party’s Website. 2018 . Cabinet approves doorstep delivery of ration under PDS , March 6. [https://aamaadmiparty.org/cabinet-approves-doorstep-delivery-of-ration-under-pds/].Last accessed June 23, 2020. Return to Text. 8. Govt of NCT of Delhi v. Union of India, Civil Appeal no 2357 of 2017. Return to Text. 9. Mander, H. et al. 2020 . A plan to revive a broken economy , The Hindu , May 14. [https://www.thehindu.com/opinion/lead/a-plan-to-revive-a-broken-economy/article31577261.ece]. Return to Text. 10. Reardon T. et al. 2020 . Covid 19’s Disruption of India’s transformed food supply chains , Economic and Political Weekly , May 02, Vol. LV, No. 18. [https://www.epw.in/journal/2020/18/commentary/covid-19s-disruption-indias-transformed-food.html]. Return to Text. 11. Ashwini C. et al. 2019 . Water Quality Monitoring Using Machine Learning And lot , International Journal of Scientific and technological Research , Vol. 8, Issue 10. [http://www.ijstr.org/final-print/oct2019/Water-Quality-Monitoring-Using-Machine-Learning-And-Iot.pdf]. Return to Text. 12. Vithu P. and Moses J. A. 2016 . Trends in Food and Science Technology, Elsevier , Vol. 56, pp. 13-20. Return to Text. References: Ashwini C. et al. 2019. Water Quality Monitoring Using Machine Learning And lot , International Journal of Scientific and Technological Research , Vol. 8, Issue 10. [http://www.ijstr.org/final-print/oct2019/Water-Quality-Monitoring-Using-Machine-Learning-And-Iot.pdf]. Basu, K. 2015 . The Republic of Beliefs: A New Approach to ‘Law and Economics’ , Policy Research Working Paper 7259, World Bank Group, Development Economics Vice Presidency, Office of the Chief Economist. [https://openknowledge.worldbank.org/handle/10986/21991]. Himanshu and Sen, A. 2011 . Why not a universal food security legislation?, Economic and Political Weekly , Vol. 46 (12), pp. 38-47. Rajagopal, K. 2020. Supreme Court orders Centre and States to immediately provide transport, food and shelter free of cost to stranded migrant workers , The Hindu , May 26. [https://www.thehindu.com/news/national/supreme-court-takes-suo-motu-cognisance-of-migrant-workers-issue/article31679389.ece]. Ghosh, J. 2010 . The Political Economy of Hunger in 21 Century India , Economic and Political Weekly , October 30, Vol. xlv (44), pp. 33-38. [https://www.epw.in/journal/2010/44-45/perspectives/political-economy-hunger-21st-century-india.html]. Ngullie, O. G. 2017. Food for the Poor: A Comparative study of the Public Distribution System and the Cash Transfer Scheme in Delhi , Unpublished Ph.D. thesis, Jawaharlal Nehru University, New Delhi. Ngullie, O. G. 2018. The Politics and Governance of Social Policies in Delhi: Comparing Cash and In-kind Transfers , Policy Report No. 22, The Hindu Centre for Politics and Public Policy, Chennai. 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