Digitalisation’s Marginalising Impact on India’s Unorganised Sector

1. Introduction

Controversies surround India’s growth performance, especially since 2015. Officially, it is now claimed that the economy is the fastest growing large economy in the world and that only 11.3 per cent suffer ‘multidimensional poverty’ (Niti Aayog 2024). Yet, the government is giving 5 kg. of grains per month per person free to 81 crore (810 million) citizens, or 58 per cent of the population, since it believes they are unable to buy enough food. Is this not an admission that growth has not resolved the issue of poverty in India? Persistence of poverty is linked to a high level of unemployment. So, if growth is robust, why is the unemployment level high?

Could it be that the official growth and poverty data are incorrect? Data from various sources suggest that there is growing income and wealth disparity in India (Oxfam, 2023). The implication is that whatever growth is taking place is narrowly concentrated in the hands of a small per cent of the population. This is characterised as K-shaped growth, especially after the pandemic.

While inequality has existed for long, it is getting aggravated because India is following a top-down development paradigm with elite capture of policies. Soon after Independence was attained, this was moderated by the national leadership’s understanding that citizens are not responsible for their basic problems, and they cannot resolve them on their own. So these problems had to be collectively resolved via active State intervention in their favour. These mitigating policies were jettisoned in 1991 with the introduction of the New Economic Policies (NEP), and that has further aggravated inequalities (Kumar, 2013).

Since 2016, inequalities have further deteriorated, due to demonetisation, the structurally faulty Goods and Services Tax (GST), and the non-banking financial corporations (NBFC) crisis. The Government pushed policies such as demonetisation and GST in the name of formalisation and digitalisation of the economy. The lockdown in 2020 and the growth of e-commerce have worsened the situation. This article analyses these policies and their impact on the economy.

2. Unorganised Sector is Very Large – Difficulty in Estimation

The economy consists of the unorganised and the organised sectors. As per the available data (GoI, 2017a), the former employs 94 per cent of the workforce and produces 45 per cent of the output. Such a large unorganised sector does not exist in any other major economy. The differences between the two sectors are in use of technology, scale of operation, wages, access to bank credit, marketing, etc..

The unorganised sector units are so numerous that they cannot be measured every year. Periodic surveys (every five years) are carried out to collect these data, which are used to estimate the contribution of this sector to the GDP. After 2015, no survey of the unorganised sector units was carried out. From 2016 onwards, this sector has been adversely impacted by the shocks to the economy, invalidating the use of the 2015 data to estimate its performance and its contribution to the GDP. GoI (2023) shows that the share of the micro, small and medium enterprises (MSME) sector in GDP has declined from 30.5 per cent to 29.2 per cent between 2019-20 and 2021-22.

Kumar (2017) and Kumar (2019) have argued that for much of the unorganised sector, independent data are not available for estimating the sector’s contribution to GDP. For most of its sub-sectors, organised sector data are used as a proxy (see GOI, 2017b). Kumar (2020) has argued that the High Frequency Indicators (HFI) used to estimate the quarterly output represent the organised sector and not the unorganised sectors. Thus, the methodology used creates an upward bias in the contribution of the unorganised sector to GDP. Both these points have now been mentioned in a Reserve Bank of India (RBI) publication (Bhowmick, et.al. 2022). They say,

… as most of the HFIs belong to the organised sector. Therefore, information pertaining to the unorganised sector a segment contributing almost half to the overall economy remains untracked due to non-availability of robust data. …. the research agenda regarding the measurement, estimation and other issues pertaining to the informal economy remains largely unexplored…

GoI (2007), analysing the unorganised sector in the early 2000s, painted a grim picture of marginalisation of this sector in the economy, stating,

…the unorganized workers consisting of about 92% of the total workforce of 457 million (as of 2004-05). For most of them, conditions of work are utterly deplorable and livelihood options extremely few. Such a sordid picture coexists uneasily with a shining India that has successfully confronted the challenge of globalization …

… a buoyancy in the economy did lead to a sense of euphoria by the turn of the last century. However a majority of the people, who did not have even Rs.20 a day for consumption were not touched by this euphoria.

What this Report said in 2007 rings true again when the Government is claiming that the economy is booming while in reality, the unorganised sector is languishing.

3. Place of the Unorganised Sector in the Economy

The unorganised sector is also referred to as ‘informal’ and ‘unregistered’. These terms refer to units that are not registered in the Government’s records. Bhalla (2009) presented the definitional and methodological issues involved. The organised (also known as ‘formal’) sector units also employ temporary/contract workers who do not have job security, written contracts and access to social security. So, the term ‘unorganised’ refers to both labour that does not have formal rights, and the unregistered production units.

The existence of a large unorganised sector in India is the result of the adoption of the trickle-down approach to development, which marginalises the technologically backward sectors. The advanced sectors, being capital-intensive, absorb most of the investment, but offer few additional jobs. The backward sectors get a small share of investment, while most workers have no choice but to work in it. This situation got further aggravated post-1991 with the advent of the New Economic Policies (NEP) based on the idea of ‘marketisation’ (Williamson, 1989 called it the Washington Consensus). This change in the policy regime further strengthened the organised sector at the expense of the unorganised sector (See Kumar, 2013).

In each broad sector, there is an unorganised sector component, which varies from sector to sector. Agriculture is almost entirely in the unorganised sector. The public sector is entirely in the organised sector. Every other sector has both components. For instance, there are hotels and restaurants, airlines and big manufacturing companies in the organised sector, while dhabas, rickshaw pullers and micro units belong to the unorganised sector.

The organised and unorganised sectors are differentiated by technology. The former use more advanced technology and pay significantly higher wages than the latter. Most of the investment in the economy goes into the organised sector which is a) much more capital intensive and b) has a much bigger scale of operation than the unorganised sector. The high capital intensity leads to low employment generation in the organised sector. So most of the workers have to work in the unorganised sector. The latter has lower productivity, and also, because the workers are unorganised, they get a lower wage than in the organised sector (for similar work).

It should be noted in this context that even a rise in wage rates does not automatically indicate improved bargaining power of workers or rising employment levels. Wage rates may rise as mechanisation in agriculture and automation in industry replace a large number of unskilled workers with a smaller number of skilled workers/employees. In that case wages may rise despite unemployment rising, as is the case at present. Further, the extent of overtime and use of contract labour in industry are not reflected in the data, so we do not get a real picture of the hourly wage rates. In short, a seeming rise in wage rates can even go hand in hand with rising poverty.

4. Shrinking of the Unorganised Sector

Kumar (2020) has argued that the share of the unorganised sector has been shrinking since 2016-17 due to demonetisation and other developments. Kumar (2023a) gives an idea of this decline in 2022-23. Using data on aggregate output per worker, productivity in the non-agriculture unorganised sector is 0.63 times average productivity, while in the organised sector it is 9.17 times. That is, the organised sector produces 14.56 times more output per worker. So a shift in demand from the unorganised to the organised sector leads to an increase in productivity per worker, but higher unemployment/under-employment.

A shift of production from the unorganised to the organised sector does raise productivity. But it also results in an increase in under-employment and disguised unemployment, with close to zero productivity. So, the average productivity in the economy hardly increases. A corollary of these trends is that, the higher the growth rate of the organised sector, the worse the brewing unemployment crisis for workers.

Elsewhere, we have argued that under certain assumptions, the decline in the unorganised sector could be between 9.3 per cent and 5.6 per cent. (See Kumar (2023a) for an elaboration of this.) The official GDP growth rate of 7.2 per cent would then be incorrect, and actual GDP growth would lie between 2.5 per cent and 3.5 per cent. In that case, the Indian economy would not be the fastest growing large economy in the world.

Again under the above assumptions, the GDP contribution of the unorganised sector, instead of growing at 6.5 per cent (the official growth rate), would be declining at upwards of 5.6 per cent a year. Thus, on an average, post 2016, its output would be less by at least 12 per cent compared to what it could have been. So, over the seven years since 2016, the loss of output of this sector would be about Rs 84 lakh crore. (Kumar (2023a))

5. Government Pushing for the Digitalisation of Economy

The Government is pushing for the digitalisation of the economy in various ways: for example, Aadhaar, direct benefit transfer (DBT), banking, Goods and Services Tax (GST), Central Bank Digital Currency (CBDC), etc. It argues that these steps will a) lead to reduction in the black economy and increased tax collections, and b) bring the economy under its control via regulation.

However, the unorganised sector cannot be formalised through such methods, given its small scale of operations. While officially it may open bank accounts and use digital payment platforms for its transactions, these measures will not turn unorganised/informal units into the organised/formal sector. The vast majority of those working in this sector have incomes way below the taxable limit. Kumar (2023d) points out that in 2020-21, only 0.68 per cent of the population were effective income tax payers. Further, 0.016 per cent declared an income above Rs.1 crore, and their share of the taxable income was 38.6 per cent. Clearly, even most of the organised sector were not effective tax payers.

There are 30 crore (300 million) unorganised sector workers registered on the e-shram portal, and 94 per cent declare an income of below Rs 10,000 per month, or Rs 1,20,000 per annum, which is 16 per cent of the current level at which tax has to be paid. Only a few owners of unorganised businesses (say, dhabas and shop owners), and very few workers, would be in the tax net.

So, an increase in direct tax collections indicates the growth of the organised sector, and not of the economy as a whole, as the Government claims. Further, since demand is shifting to the organised sector, leading to an increase in its share of the economy, it cannot be concluded that the unorganised sector is becoming organised or formalised, and that tax collection is rising as a result.

The shift in demand from the unorganised sector is akin to its being colonised. During colonial rule, the coloniser captured the markets of the colonised nations. In India, capitalist growth is occurring at the expense of pre-capitalist formations in agriculture and the small producers.

Since the formal and organised sector is dominated by large corporations, and many of them are multinational corporations (MNCs) or with substantial investment by the MNCs and foreign portfolio investors (FPI), control of the economy is slipping into the hands of international finance capital. Since the operations of MNCs are more digitised, greater digitalisation of the economy will favour them.

Implications of Digitalisation for ‘Welfare Rights’.

Digitalisation is leaving behind many of the marginalised, who do not have access to the internet or devices such as computers and smart phones, and/or have low financial literacy. At times, even if they own devices, the connectivity is poor, so they cannot access the net. This is the internet divide. So those with limited access to internet not only cannot benefit from digitalisation, but may suffer due to inability to access services.

The digitalised systems are also not foolproof. Many kinds of errors are encountered. For example, mismatch of fingerprints or iris scans may occur during authentication. Many elderly persons have had difficulty in getting their fingerprints registered, due to age-related factors. Many workers doing heavy manual work find that their fingerprints get disfigured, as a result of which they cannot authenticate the transaction. At times, the software malfunctions, and authentication is denied. Further, due to fraud, fake accounts are created, resulting in problems for genuine persons. Scamsters are also stealing and misusing the identities of people, leading to hesitancy among people.

Due to these reasons, ‘welfare rights’ are being denied to some poor people covered by various schemes – for example, direct benefit transfers for cooking gas subsidy, payments to farmers, health benefits, ration, etc. In brief, digitalisation is a double disadvantage to many of the poor. First, it marginalises them, and second, they are often unable to avail of their legal rights.

6. Flawed Methodology to Estimate Unorganised Sector

Kumar (2023c) analyses the ‘Methodology of Compiling Quarterly GDP Estimates’ presented in GoI (2017b). Three noteworthy aspects of the method to calculate GDP from the supposedly more accurate ‘production side’ are as follows:

1. “The production approach used for compiling the QGVA [Quarterly Gross Value Added] estimates is broadly based on the benchmark-indicator method.”

2. “In this method, for each of the industry-groups, estimates of GVA [Gross Value Added] are compiled ….”

3. “In general terms, quarterly estimates of Gross Value Added (GVA) are extrapolations of annual series of GVA.”

To put it simply, in a specific year, data are directly collected about the output in the organised sector and the unorganised sector, and the relationship between the two is benchmarked. In subsequent years, data regarding the unorganised data are not directly collected; rather, organised sector output data, which are available at more frequent intervals, are used to estimate the output of the unorganised sector, on the basis of the earlier observed relationship. This method continues till a fresh survey of the unorganised sector takes places, which is usually done at five-year intervals, though at present there is a longer gap.

Thus for the quarterly estimates of GDP, based on the production approach, current data are mostly not available. So ‘benchmark indicators’ from an earlier reference year are used. The last survey of unincorporated enterprises was carried out in 2015-16 (GoI, 2017a). So a dated reference year, that does not capture the current reality, is being used.

Further, the methodology states that current figures are obtained by ‘extrapolations’ of the annual series of GVA. But, if the previous year figures are incorrect, how can their extrapolation be correct? Especially when demonetisation, introduction of GST, and the Covid lockdown administered shocks to the economy that caused disruptions (see sub-section below).

a. Shocks Undermine the Method

The methodology outlined above relies on a smoothly functioning economy. But it will not apply when there are big unexpected changes, called ‘shocks’, such as demonetisation or the sudden lockdown. Shocks have the following impact:

i) The basic parameters of the economy change, such as the ratio of the unorganised to the organised sector, or the size of the agricultural output.

ii) Hence the validity of the ‘benchmark-indicators’ comes into question.

iii) Extrapolation from a normal year to the next one that has experienced a shock would not be correct. Nor would the extrapolation from the year of shock to the next one.

The Indian economy has suffered several shocks since 2016. Demonetisation in 2016 (Kumar, 2017), the introduction of the structurally faulty GST in 2017 (Kumar, 2019), the non-banking financial corporations (NBFC) crisis in 2018, and finally the sudden lockdown in 2020 (Kumar, 2020). Each of them impacted the unorganised sector far more than it did the organised sector, thereby changing the ratio between the two and invalidating some of the ‘benchmark indicators’. Subsequently, units in the unorganised sector either did not recover at all or did so very slowly. So, even after the economy recovers, the indicators remain incorrect.

b. Shocks and Digitalisation

Demonetisation was carried out on the ground that the black economy needed to be checked (Kumar, 2017). Very quickly, it was realized that this policy objective would not be achieved, since the basic premise underlying demonetisation was incorrect. So the goalpost was shifted to making the economy ‘cashless’. It was assumed that people would be forced to give up use of cash and would shift to the digital mode and banking channels, which would leave a trail that the authorities could track.

Not only were the initial objectives of demonetisation not achieved, but the currency in circulation has shot up in spite of the rapid rise in digital transactions. As pointed out in Kumar (2017), the lasting impact has been the decline of the unorganised sector.

In July 2017, the structurally faulty GST was introduced (See Kumar, 2019). GST is calculated as a value added tax (VAT), which requires details of inputs and output. It can only work with computerisation. So it was expected to give a strong push to digitisation. All accounts of businesses were expected to become available for scrutiny by the tax authorities, thereby curbing the black economy. But, for the small and the micro sector, computerisation of accounts is too costly, given their small scale of operations. That is why producers with a turnover of less than Rs 50 lakh are exempted from GST, and if the turnover is up to Rs 1.5 crore, they are under the Composition Scheme.

In both these cases, they are not eligible to claim Input Tax Credit (ITC), and firms purchasing from such units too cannot claim ITC on those purchases. This puts the unorganised sector units at a disadvantage vis-a-vis the organised sector. (For example, let us take the case of a small unit that supplies inputs to a large manufacturer at Rs 95, and a large supplier that supplies them at Rs 100. However, only the large supplier is able to provide ITC to the large manufacturer. In that case, the effective price of the supplies from the large supplier will be lower, and therefore the large manufacturer will purchase only from the large supplier.) As a result, unorganised sector units have lost market share. A shift in demand away from the unorganised sector is reported in industries such as fast-moving consumer goods (FMCG), leather goods, luggage, and pressure cookers, and in the services sector, such as retail trade. (Kumar 2022b)

The organised sector continues to generate black incomes despite GST because of the complexity of the law and the existence of loopholes. The result has been much litigation and hundreds of changes in the laws. Fake companies to claim fictitious ITC, mispricing of produce, manipulations in e-way bills and so on are being routinely discovered. The Government revealed in the Rajya Sabha that cases of GST evasion detected had steadily risen from Rs 41,000 crore in 2019-20 to Rs 1.51 lakh crore in April-October 2023, but the rate of recovery had fallen from 45 per cent to 12 per cent (Rajya Sabha Unstarred Question no. 225, December 5, 2023).

So, while GST has forced computerisation, black income generation continues.

The sudden lockdown reduced mobility and forced people to use more of digital transactions. E-commerce, electronic payments, etc., have increased, further marginalising the unorganised sector. The government used this crisis to push its agenda of digitisation and marginalisation of workers and the farmers. The introduction of the three farm laws and implementation of the labour code are examples of this agenda.

7. Unorganised Sector Invisiblised in Data and Policy

The unorganised sector is a residual sector. If a worker does not find work in the market then she/he has to resort to self-employment to sustain self and family. For instance, workers may do headload work or pull a rickshaw. Indigenous people may collect a little bit of the forest produce and sell it at the local market or in the nearby city.

The unorganised sector is large and amorphous and beyond Government control/regulation. The Government seeks to change this through formalisation, that is, it wants that these producers be registered, use banking channels and pay taxes. But the scale of operation in this sector is tiny. The 73^rd Round of the National Sample Survey found that there were over 63 million unincorporated enterprises in India in 2015-16, employing 111 million workers in manufacturing, trading and other services, with an average employment of 1.7 and Rs 2.3 lakh of fixed assets per enterprise. More than 84 per cent of these enterprises, employing 62 per cent of the workforce, were ‘own account enterprises’ (OAEs), without a single hired worker. The remaining enterprises, with at least one hired worker, are termed ‘establishments’. Establishments hired an average of only 4.2 workers per enterprise, and had a Gross Value Added of only Rs 6.4 lakh per enterprise per year. (GoI, 2017a) Hence most units in this sector have difficulty in registering, digitising or using banking. Even when they do get registered, these producers will remain small and will not turn into the organised sector – they only get damaged by having to comply with the burdensome processes.

Kumar (2023d) points out that India’s tax base is small. Till 2022-23, income tax was to be paid at incomes 4.5 times the per capita income at current prices. Thus, the vast majority of the unorganised sector incomes lie below the taxable limit, whether they are reported or not. Further as mentioned above (Section 7b), the unorganised sector is largely exempted from GST.

Thus, this sector is mostly outside the direct and indirect tax net. A rise in the tax collection reflects the growth of the organised sector, and not the economy as a whole.

As argued above, the Government’s attempt to formalise this sector has only damaged it, and that hurts the rural economy and agriculture, which are the largest employers. Agriculture produces the basics of life which everyone requires. So, a large part of demand for agricultural produce comes from the unorganised sector itself. As the incomes in the unorganised sector decline, demand for agricultural produce falls. That is reflected in malnourishment and under-nourishment and high stocks of foodgrains. This leads to lower prices of agricultural produce and lower incomes for the farmers, workers and rural producers. In a vicious cycle, demand and incomes across the unorganised sectors decline (See Kumar, 2022a).

Since the GDP data does not capture the decline in these incomes, the government is in denial about the deteriorating economic situation. Consequently, policy makers do not feel the need to help the unorganised sectors.

So, the unorganised sector is invisiblised both in data and in policy.

8. Macro Variables Impacted by GDP Errors

GDP data are used to estimate other macroeconomic variables, such as consumption and investment. So errors in one lead to errors in the other. The unorganised sector mostly produces consumption goods, such as food and items of day to day consumption, especially, for the marginalised sections. Production of capital goods is largely in the organised sector. The over-estimation of GDP contribution of the unorganised sector means that consumption goods production is over-estimated. (Estimation of investment would not be impacted by this factor, since both GDP and consumption are over-estimated by the same amount.)

Since the unorganised sector employs 94 per cent of the workforce, its decline causes growing under-employment, disguised unemployment and workers dropping out of labour force. So, while more people seek work in this sector, their income is over-estimated and poverty is more than depicted. Kumar (2022a) estimates that in 2021-22, 280 million workers did not have proper work.

Finally, growth in the organised sectors at the expense of the unorganised sector accentuates disparities. This inequality is not just between capital and labour but also between the owners of big business on the one hand and the owners of small and micro businesses. In per capita income terms, the economy is at 138^th position in the world, but given the rising inequality, even this low average does not reflect the actual living standard of the marginalised.

Impact on Poverty Estimation

The problems in employment pointed to above lead to fewer members of the household earning incomes, and that causes increase in family poverty. Inflation adds to the woes of the poor by reducing the purchasing power of their already low wages. This leads to further decrease in demand which results in economic slowdown..

Even if the unorganised sector incomes stagnate, poverty cannot be declining. But, the Government claims a reduction in ‘multi-dimensional poverty’ between 2015-16 and 2019-21 on the basis of data from the National Health and Family Surveys (NHFS). Kumar (2023b) points out this cannot be correct, given that the terminal year is the pandemic year, 2020, when most children were out of school; there were many additional deaths and illnesses and for a vast majority of citizens; and the standard of living fell as their incomes declined.

In brief, given that the level of income, consumption and employment in the unorganised sector is less than depicted in the official data, poverty has to be greater than what is officially stated.

9. Black Economy and Marginalisation

Digitisation was supposed to curb illegality by making systems foolproof. Instead, new kinds of illegality have surfaced while the old forms of illegality and fraud continue. In India, the black economy is concentrated in the hands of the top 3 per cent of earners, who benefit from it at the expense of the 97 per cent (Kumar, 1999 and Kumar, 2017). Thus, income distribution is much more skewed than revealed in the white economy data. The black economy has an impact on a number of aspects of the macroeconomy – the level of inflation, the productivity of investment, the availability of Government resources for welfare schemes, and the extent to which welfare schemes actually reach targeted beneficiaries. Finally, it affects the social and political system itself.

Kumar (1999) points out that the solution to this problem is not economic or technological. That is why the hundreds of economic and technological measures tried over the last 75 years have not been able to check the growth of the black economy. Even digitisation has not yielded results. For instance, measures undertaken like, demat accounts, Aadhaar, and PAN have been circumvented in connivance with those in charge of the schemes. (Kumar, 2017). But the Government has resisted moves to bring its top functionaries under the purview of RTI, and to strengthen the whistle blowers’ protection.

Black incomes are generated largely by high income earners who belong mostly to the organised sector. The organised sector is considerably digitised, but that has not stopped it from generating black incomes via under- and over-invoicing. (Firms routinely understate or overstate the price of a sale or a purchase in order to transfer funds illicitly. This is done in particular with exports and imports. However, the digital record shows only a legitimate transaction.) Digitisation by itself has not checked black income generation.

If the black economy had been dented due to the steps undertaken by the government in the last 9 years, the direct tax/GDP ratio should have risen substantially. (Kumar, 2023d) shows that the ratio has continued to hover between 5.75 and 6.1 per cent, indicating that the black economy in India has not been dented.

10. Growing Inequality and Demand Shortage

Digitalisation has resulted in the strengthening of Capital against Labour. Capital has become highly mobile since the 1980s, and that enables it to extract concessions from national and sub-national governments, such as to dilute labour laws. The result has been a decline in the wage share in value of output of the corporate sector (Kumar, 2007 and Goldar, 2013).

Inequality increases as the organised sector grows at the expense of the unorganised sector. This inequality is not just between Capital and Labour, but also between the owners of big business on the one hand and the owners of small and micro businesses. Further, multinational capital’s share in the financial markets and in ownership of Indian companies has grown over time, and that also aggravates inequality.

These varying kinds of inequality have major macroeconomic consequences. Importantly, a shortage of demand persists, which slows down growth. This was evident in the pre-pandemic period of the last quarter of 2017-18 to the last quarter of 2019-20. For eight consecutive quarters the official rate of growth dropped from 8 per cent to 3.1per cent. The result was that, according to the RBI, capacity utilisation in industry hovered at about 73 per cent. These are figures pertaining only to the corporate sector. The slowdown occurred in spite of the huge concession in 2019 in corporation tax, amounting to Rs.1.6 lakh crore in the first year itself.

This concession reflects the Government’s bias. It seeks to tackle inadequate demand by offering more concessions to businesses. What was required was more incomes in the hands of the marginalised, and not more concessions to Capital. It makes it obvious that the Indian State is working against the interest of its citizens, most of whom work in the unorganised sector.

11. Conclusion

Digitalisation and formalisation are projected by the Government as a solution to the Indian economy’s problems, such as tackling the black economy and improving tax collection. Towards this end, the Government has taken various steps such as demonetisation, GST, Direct Benefit Transfer (DBT) and Aadhaar. While the goals set for these steps have not been achieved, new problems have emerged, since the unorganised sector has been adversely hit.

It is pointed out that the non-agriculture unorganised sector is not independently estimated in the GDP and is proxied by the growing organised sector. Demonetisation, GST and lockdown administered shocks to the economy and rendered invalid the method of estimating the contribution of the unorganised sector to the GDP. The shocks led to a disproportionately large adverse impact on this sector compared to the organised sector.

Further, while the organised sector recovered, the unorganised sector could not do so due to these repeated shocks. Thus, using the organised sector as a proxy for estimating the unorganised sector is incorrect and leads to an overestimation of GDP and other variables such as consumption. The result is an underestimation of inequality and poverty in India.

It is pointed out that the economic units in the unorganised sector are too small to get formalised, even if they start transacting through banks and digital mode. So digitisation has further damaged this sector without formalising it. This has proved to be a costly mistake, since demand has been shifting from the unorganised to the organised sector. This is like colonisation. Given that the organised sector is more capital intensive than the unorganised sector, the demand shift has resulted in decrease in employment generation, under-employment, disguised unemployment and persistence of poverty. It has resulted in greater inequality and shortage of demand which has led to the economy slowing down.

The Government’s promotion of digitalisation represents its policy bias in favor of the organised sector. The multinational corporations (MNCs) prefer a more digitised economy since it is advantageous for them.

Since the unorganised sector is not independently estimated, it is invisiblised in data. It enables the Government to claim that Indian economy is the fastest growing large economy and nothing is wrong with it. So no special steps are required to help the declining unorganised sector. Thereby it gets invisiblised in policy also.

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