August 2021
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COVID-19 Compendium (August 2021): Official Information on COVID-19 Released by India and the WHO [HTML and PDF]

An up-to-date compilation of official information released by the Government of India from January 17, 2020, and the World Health Organisation (WHO).

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Resource: Energy Statistics 2021 [PDF 5.07 MB]

The full text of the report, Energy Statistics India 2021, can be accessed here:

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Parliamentary Report: Bridging the COVID-19 Learning Gap in Schools [PDF 1.44 MB]

The full text of the report, "Plans for Bridging the Learning Gap caused due to School Lockdown, as well as Review of online and offline Instructions

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Resource: Persons with Disabilities (Divyangjan) in India - A Statistical Profile : 2021 [PDF 10.3 MB]

Persons with Disabilities (Divyangjan) in India - A Statistical Profile : 2021, can be accessed here:

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Resource: National Monetisation Pipeline Volume I and Volume II

In July 2021, the Niti Aayog prepared a National Monetisation Pipeline "to provide a direction to the monetisation" of public assets. The two-volume

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Pandemic-induced Poverty in India after the First Wave of COVID-19: An Elaboration of Two Earlier Estimates

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. HTML version [PDF 438 KB]   Related Articles Published in The Hindu Centre for Politics and Public Policy: 1. Priya, R. et al., 2022 . COVID-19: Urban Middle Class Survey Highlights Need for People's Agency in Policy Making , February 18. 2. Souza, P. D. S., et al., 2021 . The Supreme Court of India's Vision for e-Courts: The Need to Retain Justice as a Public Service , July 10. 3. Shankar, G and Kiumari, R. 2020 . The Migrant Economy During the Pandemic: An Exploratory Study in Baisi Block, Bihar , December 10. 4. Jacob, N. 2020 . Sewage Testing as a Pandemic Monitoring Tool , September 10.

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Pandemic-induced Poverty in India after the First Wave of COVID-19: An Elaboration of Two Earlier Estimates

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 1,478 1,514 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 3,251 2,778 6,410 5,477   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 Headcount Ratio .0723 .1499 .0776 0 .0162 .0162 .0561 Aggregate Headcount (in millions) 63.91 132.51 68.60 0 7.71 7.71 76.31 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 2,900 3,344 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 ₹) PRC APU PRC ACU 1,478 2,900 1,514­­­­­­­ 3,344 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 5,060 3,997 7,692 5,692   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 Headcount Ratio .2646 .4187 .1541 .1631 .3391 .1760 .1618 Aggregate Headcount (in millions) 233.91 370.13 136.22 77.64 161.41 83.77 219.99 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].

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Cooperatives Need a Regenerative Movement More than a New Ministry

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. HTML version [PDF 326 KB]

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Cooperatives Need a Regenerative Movement More than a New Ministry

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 & Thrift 20.79 Housing 17.83 Dairy 17.79 Labour 5.50 Agri-Allied & Livestock 3.50 Consumer 3.08 Women/Tribal/SC&ST 2.52 Textile & Handloom 2.05 Industrial 2.03 Multi-Purpose 1.75 Others 23.02 Multi-State Coops 0.15 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  181190 318700 854355 Total Members (Million) 13.7 148.0 290.1 % of members to total population 3.8 % 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-Credit 13.4 Fertilizer Production 28.8 Fertilizer Distribution 35.0 Sugar Produced 30.6 Milk Procurement 17.5 Storage Capacity 14.8 Spindleage 29.3 Direct-Employment 13.3 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 [email protected]' (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 [email protected]", 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.