Journal of Migration Affairs
Vol. III(1): 16-31, Sept. 2020
Pdf Issue: Economic Implications of Reverse.pdf
The COVID-19 pandemic has been negatively impacting the entire world economy unprecedentedly, and India is no exception. To prevent the spread of COVID-19, the Government of India declared a nationwide lockdown on March 24, 2020. Sure enough, in a country where 90 per cent of the workforce is attached to the informal sector without adequate social security, such a sudden declaration of lockdown was bound to have a disastrous effect. The situation is, predictably, even worse for migrant labourers who constitute a large section of these informal workers. As can evidently be inferred from the daily news and information from relevant sources, the response to the pandemic threatens to worsen the already-convoluted economic crisis in the country, the extent of which is far more long- lasting and deep-rooted than the direct impact of the pandemic itself. This article tries to explain the dynamics associated with the incidence of reverse migration. It attempts to visualise the incidence of reverse migration in the context of mainstream development theories. It also tries to understand the extent of reverse migration under the COVID-19-led crises. Since there is no official data available to measure the precise extent of reverse migration, this study will draw upon other sources of estimations in this regard.
Further, this study tries to analyse and explain the extent to which such reverse migrants could be accommodated in their source regions. In doing so, the existing rural infrastructure is assessed and explored in terms of its capabilities and preparedness for adjusting to such an inflow of labour. In order to have a complete understanding of the different labour dynamics set in motion by the process of reverse migration, this paper compares the altered scenario at both the source and the destination of migration. This analysis is followed by the evaluation of current policy responses by the government, accompanied by some suggestions regarding short-term as well as long-term policies.
Reverse Migration in the Context of Development Theories
The extent of the reverse migration that has taken place makes one revisit the country’s development paradigm in the context of the standard economic theories dealing with migration. For instance, as envisaged by many (Lewis 1954; Nurske 1953; Kuznets 1966; Clark 1940; Harris and Todaro 1970), a structural transformation of any economy, from traditional/primary/ informal/unorganised to modern/industrial/formal/organised, requires a shifting of labour from the former to the latter. Migration of labour has been identified as the critical factor triggering such changes, the wage differential being the main driving force. Thus, many economists agree that labour migration can be viewed as a major determinant of structural transformation of the economy.
However, a careful glance reveals that such models of development have largely failed in the context of the Indian economy (Jha and Thakur 2017). In the last few decades, migration of labour from rural to urban sectors has been quite evident, but the share of formal/organised- sector employment in the total employment taken up remained dismal (less than 10 per cent1 of the total workforce). Recent trends show that sectors that had claimed to be responsible for absorbing the surplus labour from the agricultural sector are already dispelling labour. In the Indian economy, the Lewisian modern sector is conspicuous by its absence from the scene when it comes to absorbing the surplus labour from the agricultural sector. For instance, there has been a sharp decline in employment in urban manufacturing and construction sectors, in that order. Even though there had been an increase initially in both sectors, one can discern a steady decline in employment from 2013 onwards.2 However, there was a marginal increase in employment in the services sector by around 2.9 lakh, during 2012- 2016, though it occurred mainly in the unorganised sector (Abraham 2017). The data makes it evident that labour was hit not only by the stagnancy in the capacity to absorb additional labour in the major sectors in urban India but also by a further decline of labour conditions in these sectors. Besides, a fall in the real wages in urban sectors has also been witnessed, mostly since 2014 (Anand and Azad 2019).
Arguably, almost all migration-led development models emphasise higher and increasing wages in the urban formal sector as the driving force of migration in the economy. In the Indian scenario, the wage differential was primarily the reason for migration during the Green Revolution. However, recent studies show that the wage differential in rural India in different regions and states has come down significantly (Das and Usami 2017) and consequently the wage differential can no longer be considered the main driving force of migration from rural areas. Some of the reasons for the narrowing wage gap between different regions of the country have been identified as the enactment of Mahatma Gandhi National Employment Guarantee Act, a rise in construction activities, and the rising agricultural productivity in rural India, particularly since 2016 (Himanshu and Kundu 2017). Furthermore, field evidence at the destination of migration also indicates a worsening of working conditions for these migrant labourers, caused by various factors such as a rise in the commission charged by the middlemen facilitating migration, longer working hours, the predominance of piece-rate payments, rising share of children in the migration stream and various indications of an increase in the degree of unfreedom (Deshingkar and Akter 2009). This clearly indicates that the mobility of workers in India is not because of higher net daily earnings and better working conditions, thereby confirming the fact that migration is primarily happening due to the expulsion of labour from the traditional sectors; there is little evidence of any pull from the modern and urban sector. Evidence shows that an overwhelming proportion of these migrants work in the informal sector, which means that migration has largely remained ineffective in shifting the workforce from the informal to formal sectors or from agricultural/ primary to industry/secondary sectors. Therefore, migration in India can hardly be perceived as the source of structural transformation, enabling upward income-mobility of the working class in general. Instead, it is an indicator of the acute distress prevalent among the labour class in general. At best, it offers a partial relief in terms of providing additional income to distress-afflicted households in rural areas. It fails to catalyse structural changes in any manner in the workforce. Even before the COVID-19-induced crises, there was enough evidence reflecting a clear trend of deteriorating working conditions in urban India, particularly in terms of providing quality employment.
In fact, the COVID-19 crises have only exposed the extent of distress that already existed in the economy for long. In other words, despite the high growth rate of the economy sustained over more than two decades, an overwhelming proportion of the workforce of the country remained engaged in the informal sector with no social security. Consequently, they failed to accumulate enough savings to survive even for a week in the absence of employment. This brings us to enquire about the extent if at all, to which the vast pool of reverse migrant labourers could be accommodated in their native places in rural areas and the economic implications of such reverse migration on both the rural and urban economies. The lockdown’s economic implications can only be comprehended by analysing how India’s labour market dynamics have been altered by the massive influx of reverse migrants back into the rural labour market. It is neither expected nor feasible that reverse migration might be a permanent phenomenon with no scope for the workers to return to their destination of migration in future.3 The next sections will deal with some of these issues.
Understanding the Numbers
Before analysing the short-term or long-term impact of the COVID-19-induced reverse migration, it becomes imperative to understand the possible extent of reverse migration. There are primarily two migration data sources in India: the Census and the National Sample Survey Office (NSSO). Census 2011 puts the number of total internal migration at 45.57 crore (455.7 million), in which work-related migration was a little more than 4.5 crore (45 million), including self-employed persons. The Census figure, 37% of the total population, alarming as it is, is estimated to be far short of actual numbers. This is especially true for work-related data because the Census, while calculating total work-related migration, summarily ignores short term and circular migration which constitute the largest proportion of migrant labour in India. The NSSO, on the other hand, includes many types of such seasonal migration, though it still ignores some of the aspects of short-term migration, including rural-rural circulatory migrants in commercial farms and plantations or rural-urban migrants who migrate for a few months a year at specific times to work in small industries, or even short-term seasonal migrants who migrate for more than six months (Deshingkar and Akter 2009). Despite such omissions, the NSSO’s estimation on migration is considered more accurate and closer to the actual number than that of the Census. Unfortunately, no survey has been conducted by the NSSO on migration since 2008, and we have no actual data on migration as of now.
A few recent studies have attempted to arrive at closer estimations of migration, focusing on work-related migration. The Economic Survey 2016–17, using railway records, puts the size of inter-state migration at higher than 60 million. Recently, Professor Amitabh Kundu and his team came up with a new estimate of migration based on Census 2011, NSSO survey methods, and some guidelines to making such calculations given by the Economic Survey 2017. His estimates put the number of work-related interstate migration at about 80 million;4 this number goes much higher if intrastate migration is included. However, in the absence of a pan-Indian official record of such migration, the estimation of its actual size is subject to speculation.
A vast proportion of these migrants are attached to the informal sector where employment is mostly casual/contractual and therefore, devoid of any job security. During the lockdown, the informal sector of the economy was severely hit, and employment options reached an all-time low for informal workers, forcing them to struggle for mere survival. Having no other alternative, many of these migrants had to move back home. Their distress can be assessed from the long on-foot marches they undertook, resulting in severe health problems, and even death in many cases, on the way. In the later phases, a sizeable number of other migrants who had stayed back at destination lost their savings totally and added to this pool of reverse migration, converting it into the biggest distress-driven migration since the country’s partition.5 There are various estimates of the possible extent of such reverse migration: Amitabh Kundu and his team put this number at nearly 18 million, and there is a possibility of an additional 4 million being included in this number.6 Shridhar Kundu puts this figure at higher than 23 million,7 Chinmay Tumbe puts the figure at least 30 million.8 Most of these migrants belonged to the states of UP, Bihar, MP and Odisha9. According to various state- level information sources, media reports and field-based observations, it seems plausible that the COVID-19-led lockdown might have induced at least 35–40 million10 instances of reverse migration, including intrastate and circular migration.
Possibility of Absorption of Labour in the Agriculture Sector
Probably the simplest indication of structural distress in India’s agricultural sector is the mismatch between its contribution to the GDP (nearly 14 per cent) and the share of the workforce it employs (44%).11 Agriculture in India has largely remained trapped in structural bottlenecks even after Independence. A highly skewed land-ownership pattern (and consequently a high incidence of landlessness in rural areas), the lack of official recognition of tenants in Indian agriculture, abysmal basic infrastructure in most rural areas, and decreasing share of institutional credit in agriculture and allied sectors are some such bottlenecks. Although Land Reforms got a prominent place in policy documents after Independence, it was not properly implemented except in a few states (Jha 2007). Besides, the integration of Indian agriculture with the global economy under the aegis of neoliberal reforms unleashed a variety of factors that became responsible for agrarian distress in the country. Deterioration of the terms of trade for agriculture, fluctuations in the price of agricultural commodities, a fall in the share of institutional credit in agriculture, a relative fall in the share of public investment in agriculture, a sharp fall in the input subsidies, etc. were primarily the factors responsible for causing agrarian distress in the country (Patnaik 2007; Roy 2017).
The latest NSSO12 estimates show that 70% of the agricultural households’ income was not sufficient to meet their basic consumption in 2013 and a fall in the average calorie intake of the entire rural population was also evident (Thakur 2017). Furthermore, 52% of agricultural households were in debt, with the average outstanding loans during the same year being rupees 47,00013 per household (Basole 2017). The indebtedness in rural areas is mostly non- institutional, and the high-interest rates multiply the existing burden. The social implication of such misery is very well captured by the sharp rise in the numbers of farmers committing suicides in the country since the inception of neo-liberal reforms (Talule 2020).
The agrarian crises have been further accentuated by the government’s neglect of this sector in recent times. Since 2013, there has been a deflationary tendency in many farm products such as pulses, vegetables, and oilseeds (Bhoi and Dadhich 2019). This along with other factors such as a sharp fall in rural wages in both agricultural and non-agricultural sectors (Himanshu 2018), a slowdown in the growth of value-addition in the agricultural sector,14 and a sharp deceleration in the growth of agricultural credit since 2014 (Himanshu 2018), led to a substantial fall in the incomes of farmers and rural labourers (Chand 2017). Furthermore, due to creeping mechanisation and the adoption of new varieties of crops, there has been a sharp decline in the agricultural sector’s capacity to provide additional employment (Jha and Thakur 2013). In fact, recent trends reflect a negative employment elasticity in the agricultural sector since 2004 (Basu and Das 2016). In other words, there has been a consistent trend of the expulsion of labour from the agricultural sector. Himanshu (2011) and Thomas (2012) had estimated that the decline in absolute employment in the agricultural sector was nearly 20 million between 2004–05 and 2009–10; Mehrotra et al. (2014) estimated this number to be about 13 million during 2009–10 and 2011–12. The more recent estimates show that such a fall in absolute numbers has been continuous, and between 2013 and 2016, nearly 8.5 million workers moved out of the agricultural sector (Abraham 2017).
Thus, India’s agricultural sector has arguably been witnessing severe distress for long, and its capacity to maintain even existing employment seems extremely doubtful. There is hardly any possibility of absorption of additional labour brought in by the ‘reverse migration stream’. Furthermore, due to the increasing pace of urbanisation, since 1990, there has been a consistent trend reversal in land use for agriculture. The area under cultivation has been decreasing since then, and the rate of decline has been sharper during the more recent decades (Rathee 2014). Obviously, this places further limitations on the farming sector, and chances of it absorbing additional labour in the near future are practically non-existent.
Possibility of Absorption in the Rural Non-Farm Sector
There has been some expansion in the workforce in the rural economy in non–farm sectors. However, how far such expansion can facilitate the absorption of labour brought in by reverse migration needs to be analysed. The expansion in the non–farm sector, it has been argued, is also a shift from the agricultural to the non-agricultural sector. Several studies show that agrarian distress has forced out a large number of labourers from the agricultural sector. They either join the non-farm sector as labour or become self-employed in the non-agricultural sector. The visible rise in the share of the self-employed from 2004 to 2009 and 2012 to 2015 has been primarily attributed to agrarian distress (Abraham 2017; Himanshu 2011; Jatav and Sen 2013). Another indicator reflecting this reality has been the nearly stagnant share of formal employment in rural India. Manufacturing sector’s share in the total rural non-farm employment has been declining continuously from nearly 32% in 1994 to 22% in 2010 and nearly 17% in 2015 (Papola and Sahu 2012). While construction and trade witnessed an increase in their share in rural non-farm employment (Basole 2017), they largely remained under the informal economy. Thus, the possibility of these sectors providing additional quality jobs also remains questionable. The situation seems even more unfavourable due to the deceleration in the growth of rural non-farm wages, especially recently.
Thus, it is evident that the rural non-farm sector’s scope in providing quality employment has remained limited for more than a decade. There is little evidence of a pull-factor in the non- farm sectors in rural areas that could attract a sizeable workforce from agriculture and provide them with a better livelihood. In fact, any such expansion/shift has primarily been a means for additional income whereby members of the agricultural workforce have diversified their income by opting for some additional occupation to supplement the meagre wages/ income from agriculture. It can hardly be counted as an alternative source of employment. The ‘India Rural Financial Inclusion Survey’, conducted by the National Bank for Agriculture and Rural Development (NABARD) in 2018, states that for the marginal farmer,15 the share of the total income attributable to cultivation amounted to lower than 35 per cent of their average income. In India, more than 65 per cent of the farmers come under this category. Thus, one cannot expect the non-farm sector in rural areas to absorb additional labour in any substantial manner.
Deepening of the Crises and Changing Labour Market Dynamics under the Lockdown
As mentioned earlier, the Government of India announced a complete lockdown of the country on March 24, 2020 as an immediate response to the threat of COVID-19. The announcement was too sudden for the various stakeholders of the economy to be prepared for the subsequent difficulties. The lockdown in its fullest form remained active for more than two months, after which it continued with some relaxations until June. The lockdown happened at a time when the entire economy was already struggling with recessionary tendencies. The GDP growth rate had already touched the lowest point in more than a decade, the rate of unemployment was the highest it had been in the last couple of decades,16 the rate of growth of manufacturing was nearly stagnant, there had been a sharp deceleration in the growth of exports, and agrarian distress was probably at its peak.17
Hence, the Indian economy was not resilient enough to handle any shock when COVID-19 arrived on the scene. In this scenario, the impact of the lockdown on the economy was bound to be prolonged and distressing. In its immediate aftermath, the unemployment rate shot up, many small industrial units closed down, supply chains got disrupted (Rawal and Verma 2020), prices of agricultural commodities crashed, input costs increased along with irregularity in the supply, consumption by the entire population living at the margins registered a sharp fall, and indebtedness increased particularly from non-institutional sources.18 & 19 Thus, there has been a further deterioration in the rural sector’s ability to absorb additional labour lately, which indicates that reverse migrants are unlikely to find employment in the rural sector.
The imposition of the lockdown further restricted employment generation in both agricultural and non-farm sectors. Notably, the rural non-farm units’ business has been hit hard, as confirmed by some field-based studies20. An important implication of this is the higher level of unemployment on the one hand and a higher labour-force participation rate on the other. Some of the factors that seem to explain such high labour-force participation are: acute income deficiency causing a large number of children and the elderly—people who would otherwise be absent in the job market— to join the labour force,21 homemakers entering the labour force to supplement their family income, many households earlier engaged in non- farm activities quitting their occupation due to the falling demand in the economy and becoming part of the casual labour force, and many small and marginal farmers (facing falling incomes due to higher input price and lower output prices) seeking wage employment to supplement their income. The situation has further worsened by the influx of reverse migrants. Due to this sudden increase in labour force participation, the regions witnessing reverse migration have also experienced a sharp fall in the rural wage rate22. So, with limited job prospects on the one hand (a pre-existing situation that was further aggravated by the lockdown) and high labour-force participation on the other, high levels of unemployment and underemployment are expected to prevail, particularly in the rural economy. In this scenario, any prospect of the rural economy absorbing reverse migrants appears to be simply out of the question.
It is also important to analyse the extent to which the migration destinations—the big cities in the north and western parts of the country—would be able to reabsorb the labourers in the near future. In fact, the labourers are still not sure if their return to their native regions is short term or long term. With a general decline in production and business, the prospect of a recall of labourers post-lockdown, or after COVID-19 has been controlled, seems bleak. The actual answers to these questions will only reveal themselves once the situation is restored to normalcy. As of now, the indications and inferences from the existing facts present quite a pessimistic picture. Since an overwhelming majority of the migrant labourers work in the informal sector, their re-engagement in the same would be dependent on the extent of the revival of these sectors in the near future. However, the revival of these sectors depends on several factors, and one can hardly be optimistic on that front either.
First, a large proportion of informal-sector units could not sustain themselves for even a week after the lockdown; their savings and total capital were inadequate to make them survive even for a month.23 Quite a few of these units have perished during the lockdown. Second, many of these units are deep in debt, and the instalments for repayment of loans come from regular sales.24 This has been disrupted since lockdown happened. Therefore, repayment has become exceedingly difficult, threatening to consume the capital itself. Third, the demand in the economy is so low that even if they do start their business, with some credit relief or with other government support, there is a high possibility that they would not be able to sell their product in the market.25 Fourth, because of reverse migration, the average wage in the destination is expected to rise sharply, and most of these units cannot operate with higher wage rates. Fifth, with the possibility of a rise in wage rates in the destination, employers might move towards more capital-intensive production. One cannot rule out such a shift happening even in the North Indian region’s agricultural sector. This, in turn, might reduce the demand for labour in the rural destination areas permanently. In addition to the factors mentioned above, the uncertainty about how long these crises would continue makes the situation worse. Even large and organised units with reasonable resilience are under severe stress. There is ample evidence that economic activities, including production in most parts of the country, are happening at sub-normal levels.26 There is clearly a very little possibility of readjustment of reverse migrants in any significant manner at destinations either.
In terms of absorption of the reverse migrants, any relief would only be possible through external stimulus. The government’s role needs to be re-evaluated in containing the health threat and reviving the economy, with due consideration given to the welfare of its stakeholders.
The Role of Mahatma Gandhi National Employment Guarantee Act (MGNREGA)
In the context of the present employment crises, the Mahatma Gandhi National Employment Guarantee Act (MGNREGA), one of the country’s largest welfare schemes, can indeed be expected to play a critical role. In the short run, providing additional employment to the needy labourers can give them some relief in providing access to cash. Second, with the payment of wages under the scheme, the rural population’s purchasing power can be increased. This, in turn, might give some boost to the business of the shopkeepers or other self-employed persons in non-agricultural households. In the short term, a higher allocation of funds for MGNREGA might provide the government with some breathing space while it attempts to formulate long-term and sustainable strategies for tiding over the situation. Exploring these options, the Government of India, as part of its relief package, announced an additional allocation of INR 40,000 crore for MGNREGA on an immediate basis (total allocation in the 2020–21 budget was nearly INR 61,500 crore). This has undoubtedly been an important measure for tackling the situation, especially in the short run.
However, given the enormity of the distress, such allocation falls far short of being adequate. Even in the pre-COVID scenario, the gap between the demand for jobs and its supply had been increasing.27 In the fiscal year 2019–20, despite allocation to MGNREGA being INR 71,000 crore, nearly 7.6 million workers28 remained deprived of its benefits. However, instead of the MGNREGA funds being increased (by at least INR 15,000 crore) to fill this gap, the allocation was actually reduced by a steep 14% (by nearly INR 10,000 crore) in the 2020– 21 Budget. Additionally, the employment gap can be predicted to have been increasing further. It would not be an exaggeration to say that just to address this gap, the desired allocation in the budget for MGNREGA should have been at least INR 86,000 crore, even if we ignore the annual increment in the wage rates. Therefore, the additional allocation of INR 40,000 crore as part of the COVID relief package is not at all sufficient for absorbing additional labour. Given the scheme’s existing efficiency,29 this extra allocation can only employ 3 to 4 million additional labourers.30
Furthermore, the Central Government announced a scheme called the Garib Kalyan Rojgar Yojana, with an INR 50,000 crore allocation for providing wage employment, particularly in districts witnessing massive outmigration. However, this scheme is simply a convergence of funds from schemes already existing under different departments and ministries; not much can be expected from the scheme in terms of creating additional jobs in those areas in any significant manner. Looking at recent statistics, it is clear that since April 1, 2020, more than 20 million labourers who demanded jobs under the scheme did not get it.31 With no less than 30 million reverse migrants and a hugely inflated labour-force-participation rate (as discussed earlier), the government must realise the significance of such welfare schemes and recalculate the actual requirement of allocations to improve the number of beneficiaries.
Evidently, the unprecedented reverse migration that India has witnessed during the COVID- 19 lockdown places a serious question mark on the development discourse that the country has been following for the last couple of decades. The kind of distress that has been witnessed during the lockdown is, to a large extent, systemic. India has been largely unable to achieve a structural transformation of the workforce by catalysing voluntary movement from the low-paid agricultural or primary sector to the higher-paid secondary sector. Whatever sectoral shifting of workforce India has been witnessing is primarily attributable to the expulsion of labour from agriculture and allied sectors, with little evidence of the working class’s higher- income mobility in general. Some tertiary sectors absorbed additional labour, but since employment remained informal, this barely conforms to the Lewisian transformation. The COVID-19-led crises, therefore, not only made the situation worse but also made the entire issue more discernible. Furthermore, the magnitude of the economic stress caused by this pandemic looms large, particularly in the context of the preceding recessionary tendencies. The narrowing of employment opportunities, the rising debt burden, and the lesser allocation of funds in welfare schemes have further compounded the crises.
There is an urgent need to explore the means of dealing with this crisis. First of all, in terms of immediate action, the focus must be on providing basic healthcare facilities and preventing the spread of COVID-19—by making provisions for large-scale testing facilities and adequate quarantine facilities while ensuring the presence of healthcare providers and other infrastructure required. Second, reduction in income has had its inevitable impact in the form of a decline in consumption in a sizeable population, both in rural and urban areas. Therefore, the provision of basic minimum food at their doorstep is urgently required for their bare survival. Though the government has announced an immediate provision of an additional 5 kg of food grains per person, it needs to be extended for longer periods as well as for a wider base. Besides, there is a need to expand the existing food basket by increasing the grain quantity and including other items rich in protein and vitamins. Third, an immediate expansion in MGNREGA allocation is required to make it universal (not one-in-a-family) as well as to increase the guaranteed number of days of work (and to make it at least 200 days this year) because, as discussed earlier, more than 20 million job seekers did not get any work under MGNREGA between April and June. Besides, there is a need to increase the wage rate under the scheme as in most cases, the wage rate fixed under the scheme remains below the existing minimum wage in the concerned region. Fourth, to counter the present liquidity crises affecting a large section of people living at the margins, a sizeable increase in cash transfer is required.32 Though these suggestions can be broadly applied for the revival of the economy in general, they would be of particular help to the reverse migrants in boosting their income as well as purchasing power.
However, for medium- and long-term resolution of the problem, some urgent policy restructuring is needed. First, the primary reason for outmigration has been the push factor from the agricultural sector. So, prioritising the agricultural sector economically—through higher public investment to improve physical infrastructure and to allow for a higher allocation of institutional credit—along with adequate price support, enhancement in government procurement of agricultural produce, higher research and development grants, etc., remain key to the country’s economic development. Second, historically India has had skewed ownership of land, and the implementation of land reforms has remained an unfinished task. Higher landlessness has been one of the most critical factors responsible for the prevalence of migration.33 Redistribution of surplus lands can reduce the size of the casual labour force and substantially enhance the purchasing power of the rural population. Successful implementation and execution of land reforms in all states can also reduce the size of India’s migrant-labour force enormously. Third, efforts are required for reorienting the industrial development strategies to make them more labour-intensive and employment-generating. One needs to consider that since the enactment of neo-liberal policies in India, labour productivity has been rising, but the share of wages in total output has been declining. Similarly, there has been negative employment elasticity during this period, because of which formalisation of the workforce has been happening at a negligible pace.
Last but not least, there is an urgent need to have a sound data system that delivers relevant data at regular intervals. Historically, India has had both the Census and the National Sample Survey Organisation (NSSO) data to regularly monitor economic activities. Unfortunately, the NSSO, which happens to be one of the world’s best data systems, has become irregular in providing data under the present government. For instance, the last time the NSSO published detailed data on migration was 2007–08. Comprehensive data on employment/unemployment and consumption has not been available after 2011–12. In the absence of such data, policy formulations have suffered from several limitations constraining beneficiaries’ identification, impact assessment, comparative assessment, and long-term goal setting, and making analyses more speculative than real.
2. In manufacturing, there was a decline of 2.1 million jobs in the sector, between 2013– 14 and 2015–16 (Mehrotra et al. 2014). A similar trend was evident in the urban construction sector, which witnessed a fall in the number of jobs available by about half a million during the same period.
3. Needless to say, a large number of these reverse migrants have already lost their jobs and given the nature of their job and condition of the economy following the present crisis, there is a high possibility that a sizeable number of them would not get their job/ work back even after this crisis is over. The timeframe for the recovery of jobs will also depend on a variety of factors, and at this moment any estimation in this regard remains unreliable.
5. Many field reports for example see endnote xix, confirm such
6. https://indianexpress.com/article/explained/coronavirus-how-many-migrant-workers- displaced-a-range-of-estimates-6447840/; https://indianexpress.com/article/explained/ coronavirus-india-lockdown-migran-workers-mass-exodus-6348834/.
8. https://indianexpress.com/article/explained/coronavirus-how-many-migrant-workers- displaced-a-range-of-estimates-6447840/; https://indianexpress.com/article/explained/coronavirus-india-lockdown-migran-workers-mass-exodus-6348834/.
9. According to Census 2011, the two states of UP and Bihar constitute nearly 37 percent of total migrants.
10. Many field reports actually put the extent of interstate migration much higher than the official Some estimates put higher than 100 million. Thus the size of reverse migration might be higher than any official estimates
11. Economic Survey 2019–2020, Ministry of Finance, Government of India. Economic Survey. Economic Survey (indiabudget.gov.in).
12. Key Indicators of Situation of Agricultural Households in India, Report KI 70/ 33, 70th Round, National Sample Survey Office, Ministry of Statistics and Programme Implementation.
13. With high variability across the states. For instance, this number is as high as 93% for Andhra Pradesh.
14. Economic Survey 2018–19.
15. With land holdings of up to one hectare.
21. Many field reports such as endnote xviii and xix confirm the same. Similar findings are witnessed in most parts of the country and documented in a series of articles on COVID-19 on Newsclick. For detail, see https://www.newsclick.in/articlelist/covid-19.
28. MGNREGA, MIS.
29. With 50 percent existing efficiency.
30. 80 per cent wage cost, 100 days of work at an average wage of 180 rupees per day.
32. The central government announced transfer of three instalments of Rs. 500 to Jan Dhan Yojana holders and a total of Rs. 6,000 transfer to all farmers’ accounts.
33. UP, Bihar and Madhya Pradesh, having a skewed land distribution and higher landlessness, send more migrants out of the state than the other states.
Abraham, V. 2017. “Stagnant Employment Growth: Last Three Years May Have Been the Worst,” Economic & Political Weekly 52(38): 13-17.
Anand, I. and R. Azad. 2019. “India’s Slowdown,” Economic & Political Weekly 54(41): 11-16.
Basole, A. 2017. “What Does the Rural Economy Need? Analysis of the Promises for Rural India,” Economic & Political Weekly 52(9): 40-43.
Basu, D. and D. Das. 2016. “Employment Elasticity in India and the U.S., 1977-2011: A Sectoral Decomposition Analysis.” Economic and Political Weekly 51(10): 51-59.
Bhoi, B. K., and C. L. Dadhich. 2019. “Agrarian Distress in India: Possible Solutions.” Working Paper- WP-2019-017, Indira Gandhi Institute of Development Research, Mumbai. Clark, C. 1940. “The Conditions of Economic Progress”. London: Macmillan and Co.
Das, A., and Y. Usami. 2017. “Wage Rates in Rural India, 1998–99 to 2016–17”. Review of Agrarian studies 7(2): 4-38.
Deshingkar, P., and S. Akter. 2009. “Migration and Human Development in India.” Human Development Research Paper 2009/13. http://hdr.undp.org/sites/default/files/hdrp_2009_13.pdf.
Harris, J. R., and M. P. Todaro. 1970. “Migration, Unemployment and Development: ATwo- Sector Analysis.” American Economic Review 60(1): 126–142.
Himanshu and S. Kundu. 2017. “Rural wages in India: Recent trends and determinants.” Indian Journal of Labour Economics 59(2): 217-244.
Himanshu. 2011. “Employment Trends in India: A Re-examination.” Economic & Political Weekly 46(37): 43–59.
Himanshu. 2018. “Too Little, Too Late: Apathy towards the Rural Sector.” Economic & Political Weekly 53(9): 25-30.
Jatav, M., and S. Sen. 2013. “Drivers of Non-Farm Employment in Rural India: Evidence from the 2009-10 NSSO Round.” Economic and Political Weekly 48(26/27): 14-21.
Jha, P. 2007. “Some aspects of the well-being of India’s agricultural labour in the context of contemporary agrarian crisis,” Indian Journal of Labour Economics 49(4): 741-64.
Jha, P., and A. Thakur. 2013. “Employment and Unemployment: Context and Prospects.” In India: Social Development Report: Minorities at the Margins, edited by Mushirul Hasan and Zoya Hasan, 45-59. New Delhi: Oxford University Press.
Jha, P., and A. Thakur. 2017. “Employment Prospects for Neo-liberal India.” In Plutocary, Cronyism and Populism: Facets of Neoliberalism in India, edited by Kamal Nayan Kabra and Vrajaindra Upadhyay, 123-138. New Delhi: Vitasta Publication.
Kuznets, S. 1966. Modern Economic Growth: Rate Structure and Spread. New Haven: Yale University Press.
Lewis, W. A. 1954. “Economic Development with Unlimited Supplies of Labour.” The Manchester School, 22(2), 139-191. DOI: 10.1111/j.1467-9957.1954.tb00021.x.
Mehrotra, S. et al. 2014: “Explaining Employment Trends in the Indian Economy: 1993–94 to 2011–12.” Economic & Political Weekly 49(32): 49–57.
NABARD. 2018. “All India Rural Financial Inclusion survey.” https://www.nabard.org/auth/writereaddata/tender/1608180417NABARD-Repo-16_Web_P.pdf.
Nurske, R. 1953. Problem of Capital Formation in Underdeveloped Countries. Oxford: Blackwell.
Papola, T. S., and P. P. Sahu. 2012. “Growth and Structure of Employment in India: Long- Term and Post-Reform Performance and the Emerging Challenge.” ISID Occasional Paper Series, 2012/01. New Delhi: Institute for Studies in Industrial Development.
Patnaik, U. 2007. The Republic of Hunger and other Essays. New Delhi: Three Essay Collective.
Rathee, G. 2014. “Trends of Land-Use Change in India.” In Urbanisation in Asia, edited by K. S. Sridhar and G. Wan. DOI: 10.1007/978-81-322-1638-4_13, © Springer India.
Rawal, V., and A. Verma. 2020. “Agricultural Supply Chains during the COVID-19 Lockdown: A study of market arrivals of seven key food commodities in India.” SSER Monograph 20/ 1. http://archive.indianstatistics.org/sserwp/sserwp2001.pdf.
Roy, S. D. 2017. “Economic Reforms and Agricultural Growth in India,” Economic & Political Weekly 52(9): 67-72.
Talule, D. 2020. “Farmer Suicides in Maharashtra, 2001–2018: Trends across Marathwada and Vidarbha.” Economic & Political Weekly 55(25): 116-125.
Thakur, A. 2017. “The Dynamics of Calorie intake in Bihar,” Journal of Rural Development 36(3): 333-352.
Thomas, J. J. 2012. “India’s Labour Market during the 2000s: Surveying the Changes,” Economic and Political Weekly 47(51): 39–51.