Missing the Rich - Analysis of NSSO Data

Summary

Some of the Government statistical data published (or leaked) in 2019 created quite a stir among the academic community and even among the general public. One was the Periodic Labour Force Survey of 2017-18 which put India's unemployment rates at 6.1%, the highest in 4 decades and the other was the Consumer Expenditure Survey of 2017-18 (whose results got leaked) which showed a dip in consumption expenditure from 2011-12 to 2017-18.

The sample surveys conducted by National Sample Survey Office (NSSO) are generally regarded to provide the most authentic data about the social and economic conditions of the Indian population. These surveys cover a wide range of issues like employment, consumer expenditure, agricultural incomes, spending on education, spending on healthcare, time-use etc. Out of these, the surveys on employment (officially called the Periodic Labour Force Survey (PLFS) from 2017-18 onwards and till 2011-12 it was called Employment-Unemployment Survey (EUS)) and consumer expenditure (CES) are the most sought after. It is because the former gives a detailed idea about the unemployment rates, size of workforce, income earned by workers etc. while the latter gives itemized details about the private final consumption expenditure and is used to compute the poverty rates. 

In this article, we shall look at the incomes/ spending by the top decile of the population for 2011-12 (FY12) and 2017-18 (FY18) using data from EUS-PLFS/ CES and cross-verify it with proxies available from other sources. The other data sources refer to national account statistics (NAS) published by Ministry of Statistics and Program Implementation (MOSPI), tax returns filings data published by Income Tax Department and the wages/ salary in the organized sector from other sources. 

Data from these sources indicate two things:

1. The absolute income/ consumption (at an aggregate level) for the top decile captured by EUS-PLFS/ CES is most likely an underestimate compared to the actual numbers.
2. The growth the income/ consumption captured by EUS-PLFS/ CES from 2011-12 to 2017-18 is directionally wrong i.e., the per capita incomes/ consumption of the top decile has supposedly declined as per EUS-PLFS/ CES while in all probability it would have increased.

This is not the first time that such articles/ papers have been written. E.g., Thomas Piketty's (Source: S7) inequality database uses Tax data and others for the higher income earners (top 5-10%ile of the population) while it uses survey data for the lower deciles. However, this may be the first article (that I know of) which uses the salary data from Government and private corporate sector and also clearly shows the that from FY12 to FY18, the trend picked up by survey data is most likely incorrect.  

It should be noted that this article is not aimed at precision but to analyse the broad trends and competent academics should do better research on the same to arrive at precise estimates.  

Types of workers as per PLFS (Source S5)

1. Self-employed: Persons who operated their own farm or non-farm enterprises or were engaged independently in a profession or trade on own-account or with one or a few partners were deemed to be self-employed in household enterprises. The essential feature of the self-employed is that they have autonomy (decide how, where and when to produce) and economic independence (in respect of choice of market, scale of operation and finance) for carrying out their operation. The remuneration of the self-employed consists of a non-separable combination of two parts: a reward for their labour and profit of their enterprise.
2. Regular wage/salaried employee: These were persons who worked in others’ farm or nonfarm enterprises (both household and non-household) and, in return, received salary or wages on a regular basis (i.e., not on the basis of daily or periodic renewal of work contract). This category included not only persons getting time wage but also persons receiving piece wage or salary and paid apprentices, both full time and part-time.
3. Casual labour: A person who was casually engaged in others’ farm or non-farm enterprises (both household and non-household) and, in return, received wages according to the terms of the daily or periodic work contract, was considered as a casual labour.  

What is the problem?

As per International Labour Organization Research Brief for India dated March 2021, the regular wage earners who are protected (i.e., workers with social security etc.) have the highest level of incomes among all the classes of workers and they constituted almost 10% of the workforce in FY18. So, it would be obvious that the top decile of Indian consumers would be primarily driven by this category of workers. The other classes of workers like Self-employed workers earn only a fraction of the incomes earned by protected regular wage earners. 

 Pic 1

 

Source: S2

In the pic below, we have shown the monthly per capita consumption of the top decile (rural-urban combined) in FY12 and FY18 (both in 2011-12 prices) and the incomes of the protected regular wage earners for the same period. As one can note, the consumption expenditure fell by almost 12% in real terms and the earnings of protected regular wage earners also declined by 16%. Both seem to show a very similar trend.

    Pic 2

 

Sources: S2, S3, S4 and author's calculations

While the CES - FY18 got junked by the Government citing data quality issues, the PLFS is issued every quarter for urban areas and for every year for rural and urban areas. The reason may be that CES got its main finding incorrect (at least as per the Government) while the PLFS may have correctly estimated its main finding i.e., employment indicators like workforce participation rates, unemployment rates etc. The earnings from employment can be considered an important result, but still not the main findings per se.  

Further, as per Pic 3 below:

• Total earnings from employment of regular and casual workers (which would amount to more than 20 cr workers) was 29% of private final consumption expenditure (PFCE) in FY05 which increased to 33% in FY12 but there is a substantial drop in FY18 to 25% while even in the earlier periods it was broadly around the 30% range. However, there was a fall from 33% to 29% from FY00 to FY05 though it is not as steep as the fall from FY12 to FY18. The point to note is that even in the current PLFS data for FY23, it is around 24-25% range. It should be noted that at an aggregate level almost 50% of the total earnings mentioned above comes from the protected regular employees (though they would form just 20-25% of the number of workers).
• The total consumer expenditure of the CES (as % of PFCE which is used in GDP calculations) remained around 50% from FY05 to FY12. It should be noted in FY12, there was another recall period used which led the NSSO consumption expenditure as per that method to increase to almost 55% of PFCE (which is not shown in the below pic). The FY18 CES used followed that same methodology as the one used in FY12. However, adjusted for recall periods, there was a sharp dip to 36% in FY18. While the decline (as % of PFCE was more gradual in the earlier periods), the drop is way sharper from FY12 to FY18.

    Pic 3

 

Sources: S1, S3, S4, S5, S6 and Author’s calculations

Indications from earlier literature – The Adhikari Committee

The Adhikari Committee report dated May 2015, tried to assess the reasons for the difference between the PFCE and the CES. It should be noted that the decline has been happening over the decades. E.g., the Consumer expenditure as per NSSO was almost 95% of the PFCE in 1972-73, declined to 75% by 1983-84 and further to around 50% by 2004-05. It remained at a similar level (if we use the same recall period) from FY05 to FY12 which is a rare occurrence. 

Coming to the reasons for the differences, around 6% can be accounted by the fact that some of the notional expenses (like expenditure on account of owner-occupied dwellings, financial sector intermediation costs etc.) are not considered in CES but they are considered in PFCE. Further, PFCE includes expenditure by non-profit institutions serving households (NPISHs). Basis the data in the Adhikari Committee, even this may not account for more than 1% of the PFCE. Further, adjusted for recall periods which give better results, another 5% can be accounted. So, we still have almost 38% difference to further account for.

Then the natural question would be, which of the two is more correct. The Consumption expenditure as per NSSO or the PFCE used in GDP calculations. Well, the academics seem to take a mid-point view wherein they say PFCE is an aggregate number with a myriad number of assumptions and there may be errors in the same and can’t be used to determine poverty rates etc. Hence, for determination of consumption growth in the various strata of the population, CES should be used. 

While I understand the need to conduct CES surveys, however, the actual number may be closer to the PFCE used in GDP estimates rather than the consumption expenditure as per PFCE even though PFCE may have inaccuracies within it. The reason is simply because our GDP is primarily calculated from the production side and PFCE is largely derived from those, basically production of agricultural sector, manufacturing, services etc. While there may be some areas like the informal sector where we there are some estimation issues, even accounting for the same, our overall GDP levels may be actually quite close to where they are today (may be even higher as per some studies which say that some of the black money generated every year is not captured properly in our GDP estimations, Source: S8). So, the question is only whether it is even more that the official GDP numbers.

Further, to bolster this argument, let’s look at the aggregate consumer expenditure as per CES and PFCE for FY12 for a few select items (Source: S1):

• Motor Vehicles, Bikes and their parts: As per CES, this is INR 39,110 cr while as per NAS it is INR 95,400 cr. To corroborate NAS, one can refer to financials of some of the the main players: Maruti Suzuki’s revenues were INR 35,582 cr, Hyundai India at INR 25,400 cr, Hero Motor at INR 23,530 cr, Bajaj Auto at INR 19,893 cr, TVS at INR 7,435 cr, Eicher at INR 5,684 cr. This would include some export revenues, but just listing out the revenues of the main companies in this sector itself indicates that the CES is way off. 
• Railway spends: As per the CES, in 2011-12, the consumer expenditure on the same was only INR 5,279 cr while as per PFCE estimates it was INR 25,157 cr. The actual earnings from passengers was INR ~28,000 cr (Source: S9) which is close to the PFCE estimates.
• Air travel spends: The total spends as per CES is only INR 2,885 cr while as per PFCE it is INR 13,293 cr which would again be closer to the truth. As per financials, Indigo and Spice Jet itself earned revenues of INR 5,564 cr and INR 3,961 cr respectively. Further, Air India earned revenues of INR 14,713 cr in FY12. While these revenues would include freight and revenues from international passengers at foreign locations, still it seems to suggest that CES is way off here as well. 
• Business Service expenses (which includes Computer services, Accounting and other consultancy services etc. offered to individuals): As per CES, it is only INR 721 cr which is a gross underestimate while PFCE says it was INR 3,45,566 cr. I don’t think I need to explain much here as to which comes closer to the actuals. 
• Legal Spends: As per CES is only INR 650 cr while as per PFCE it is INR 17,066 cr. There were 1.3 advocates in India (Source: S11) and even assuming the number of advocates working in corporate law, INR 650 cr is too small a market for a million odd advocates.

This is not to suggest that CES is underestimating all expenses, it is just to show that some of the expenses are grossly underestimated. Its estimation on education, healthcare expenditure etc. is much more accurate and is even used as one of the critical inputs to calculate the actual PFCE for healthcare, education in the GDP calculations. 

Even after adjusting for the methodological differences, the reasons for growing divergence could be because the consumption of relatively affluent sections is somehow not adequately captured. There are studies by Thomas Piketty et al. (Source: S7) which suggest that India’s inequality grew faster since 1980s. As per the same, the income shares of the top 10% increased from ~30% in 1980 to ~55% in 2013. A cursory reading of this study seems to suggest that this study itself assumed that the top decile may not be reporting incomes fully or they are being under sampled during the NSSO surveys. Nevertheless, if this factor is true, it means that the wealth and incomes of the richer population grew faster than the wealth and incomes of the poorer. It should not be confused to mean the oft repeated statement: rich grow richer while poor grow poorer. The ability to capture the richer population in the sample properly may have led to this vast divergence. 

Some Smell Tests

Test 1

The CES FY17-18 (eventually junked) and PLFS FY17-18 created quite a stir. The former stated that the consumption declined in the economy in real terms from FY12 to FY18 while the latter showed the highest unemployment rates. Further, analysis of PLFS showed fall in real wages as well. A general view among academics and non-academics alike (at least a section of them) was that this was on account of demonetization and a badly implemented GST. As per them, this led to the organized sector growing at its usual pace (which showed in the GDP growth in FY17 being at 8%+ and in FY18 being close to 7%) while the unorganized sector suffering. So, the natural outcomes of this would have been:

1. A fall in real incomes of Casual workers and unprotected regular workers while the organized sector workers (which would be the protected regular workers) would have shown a growth in real incomes
2. A fall in consumption expenditure of the poorer decile while the richer deciles would have shown growth

With reference to the first point, Pic 1 shows that the opposite has happened. There is almost a 15% cumulative growth in wages of casual labourers while for unprotected regular workers the earnings have remained stagnant.

With reference to the second point (Source: S3 and S4), for the lower deciles there has been a degrowth in consumption expenditure from FY12 to FY18 for the rural population but for the lower deciles in urban population there has been a increase. Hence, on a combined basis for the bottom 50%ile, the consumption expenditure either remained the same or slightly increased by 2-3% from FY12 to FY18 as per CES. However, as can be seen in Pic 1, the fall in consumption expenditure for the top 10%ile is almost 12% which is the opposite of what one would expect.             

Test 2

As per the PLFS FY18 survey, the workforce participation ratio (percentage of workers in the total population) was 34.7%. A quick google search says that India’s population in 2017 was roughly 135 crores. Now multiplying both these figures, the total number of workers would ~47 cr. Now, out of this 22.8% were regular wage/ salary earners. This would lead to almost 10.5 crore people earning regular incomes. The average monthly earnings for this population as per PLFS 2017 was INR ~16,500 per person which translated to INR 2 lacs of income per year. Now, the cumulative earnings of these people is 10.5 crore*2 lacs per year leading to an income of INR 21 trillion per year. 

Now, as per the IT returns data for FY18 (Source: S13), 2.9 crore people reported a gross-salary income of INR 20 trillion. IT Returns could be considered as authentic as they come (of course fudging can be done there also, but it is usually on the downside). On an implied basis, it would mean that there are around 8 crore people whose earnings in FY18 was just INR 1 lakh crore i.e., just 12,500 per person per year which is a ridiculous proposition. Even if we see the incomes of the unprotected regular workers as per the workings of the ILO (refer Pic 1) (which would basically include those who work in the informal sector), it would come to almost INR 1 lakh per year leading to an aggregate income of INR 8 lakh crore for the regular unprotected workers. This itself suggests an underestimation by a factor of 30% for regular workers as a whole. 

As a caveat, it should be noted that around 15% may be on account of pensioners who are not in the workforce while on the other hand there may be salaried workers (who are protected) who don’t file returns. E.g., out of the 8 crore individuals who paid taxes (or who filed returns) only 6 crore filed their returns. There may be many in the rest 2 crore who were salaried individuals but who did not file returns. Hence, there would be an offset because of these 2 factors. Even if it is properly adjusted using better data, the larger point should still stand.

Incomes of regular wage earners – Closer to the truth

Method 1: Using the IT Returns Data

• Step 1: Take out the gross salary income as per IT Returns data for FY12 and FY18 (Source: S13). This would show (i) Salary income declared is INR 6.26 lakh crore for FY12 by 1.17 cr individuals, (ii) Salary income declared is INR 20.04 lakh crore for FY18 by 2.90 cr individuals (Source: S13).
• Step 2: As per the ILO Research Brief (Source: S2), there were 3.6 cr workers who were in the regular protected category in FY12 and 4.4 cr in FY18. It is obvious that the regular unprotected category or the self-employed category or the casual income category will not declare salary incomes. This means that out of the total regular protected workers, around 2.4 cr workers and 1.5 cr workers did not file IT returns in FY12 and FY18 respectively. For these employees, we assume they earn the average of the salaries of regular protected and regular unprotected for the respective years. The reason is simple, regular protected workers will definitely earn more than their unprotected counterparts, but since a large chunk of the high salary earners would file IT returns, for the rest, it is reasonable to assume the remainder of the regular protected employees earn somewhere between both the ranges. 

     Pic 4

Source: S2

• Step 3: Sum up both the numbers derived in Step 1 and Step 2 and adjust for CPI inflation factor from FY12 to FY18 to get the real numbers. We shall get the following summary. As can be seen below, the gap between the numbers as per the NSSO survey and the actuals is around 15% in FY12 which substantially increases to 73% in FY18. Further, on a per person basis, there seems to have been a growth of almost 27% in real terms while the PLFS data showed a dip of almost 15%.

Pic 5

Method 2: Using RBI data on Private Corporate Sector data and other sources

This basic thought behind this is that India’s regular protected employment is majorly concentrated in the Government sector and Private Corporate sector (primarily public limited companies and private limited companies). The reason being that organizations with 10 or more workers which are officially called the organized or formal sector is mainly dominated by them. As per Quarterly Report on Employment Scenario published by the Ministry of Labour & Employment (Source: S14), within organizations with 10 or more workers, almost 87.5% would fall under regular employment and most of that regular employment would be under the protected regular employment (i.e., workers with social security benefits etc.). The reason is simply because there is no reason for the unorganized sector to give social security benefits to its workers even though they may be regular workers. Hence, if we are able to track the growth in employment and salaries/ wage expenses of these sectors, we should be able to get a broad idea on how the salaries of the top decile in the country moved from FY12 to FY18. Further, if there are workers in these organizations that do not have social security benefits for some reason, their proportion in the aggregate income would be much lesser than their proportion in the workforce in these companies for obvious reasons. Now, to calculate the wage spends of the organized sector, we carry out the following.  

• Step 1: Take out the salary payments of the Central Government for civilian employees (including civilian employees working in Ministry of Defence) for FY12 and FY18. This would show (i) Salary and allowances is INR 0.95 lakh crore for FY12 for 30.8 lakh individuals, (ii) Salary and allowances is INR 1.95 lakh crore for FY18 for 31.8 lakh individuals (Source: S15).
• Step 2: Take out the salary/ wage payments of the State Governments for FY12 and FY18 (Source: S16). Select those states for which data is available for both FY12 and FY18 (since data for some states is not available for FY12) except Telangana since the state split happened only in June 2014. This would show (i) Wages/ Salaries is INR 3.24 lakh crore in FY12 which increased to INR 5.81 lakh crore in FY18. As per data available (Source: S17), there were almost 1 crore employees in these select states in 2017. It has been assumed that 97 lakh employees were there in 2012 in these states. This is the growth rate of Central Government employees from FY12 to FY18 as well. As a proxy, the number of Government and PSU employees just increased by 3% from FY12 to FY18 as per NSSO as well.
• Step 3: Take out the salary payments of the Central Public Sector Enterprises (excluding BFSI) for FY12 and FY18 (Source: S18). This would show (i) Salary expenses is INR 1.05 lakh crore for FY12 for 14.5 lakh individuals, (ii) Salary expenses is INR 1.58 lakh crore for FY18 for 10.9 lakh individuals.
• Step 4: Take out the salary payments of the Banks (both Private and Government) for FY12 and FY18 (Source: S19 and S20). This would show (i) Salary expenses is INR 0.78 lakh crore for FY12 for 11.8 lakh individuals, (ii) Salary expenses is INR 1.33 lakh crore for FY18 for 13.8 lakh individuals.
• Step 5: Take out the salary payments of the Non-Financial Private Corporate Sector. This is not so straight forward. So, we have a few sub-steps here.
• Sub (i): Take data on Employee benefits (including managerial remuneration) from RBI DBIE for FY12 and FY18 for Non-Financial Public Limited and private limited companies. This comes to INR 2.9 lakh crore in FY12 and INR 6.8 lakh crore in FY18.
• Sub (ii): Take out the approximate gross-value added (GVA) for the same set. GVA is roughly calculated as EBITDA + Employee benefits mentioned above + Staff Welfare expenses. This comes to INR 9.2 lakh crore in FY12 and INR 18.4 lakh crore in FY18.
• Sub (iii): Take out Employee benefits to GVA ratio for FY12 and FY18. This comes to 31.7% in FY12 and 36.8% in FY18.
• Sub (iv): Take out the GVA of non-financial Private Corporate Sector from National Account Statistics (Source: S21).
• Sub (v): Adjust the GVA for Quasi corporations for FY12 and FY18 (based on using appropriate sectoral growth rates) from data available for FY12 in the Changes In Methodology And Data Sources In The New Series Of National Accounts dated June 2015 published by MOSPI. 
• Sub (vi): Take out the GVA for non-financial private corporate sector. This comes to INR 19.5 lakh crore in FY12 and INR 40.4 lakh crore in FY18.
• Sub (vii): Apply the same proportion mentioned in sub-step (iii) to arrive at the Employee costs for FY12 and FY18 for the entire private corporate sector. For the sake of conservatism, we have assumed the proportion derived in FY12 remains the same in FY18 as well.
• Sub (viii): This would lead to total employee benefits in FY12 at INR 6.2 lakh crore and INR 12.8 lakh crore in FY18 for the corporate sector. In case, we apply the higher proportion of 36.8% derived in sub-step (iii) above, the FY18 figure will go up by another INR 2.1 lakh crore. This increase in employee costs as % of GVA is observed in Annual Survey of Industries as well wherein total emoluments (as % of GVA) increased from 24% in FY12 to 29% in FY19. A similar 5% increase is observed in our above calculation as well.
• Sub (ix): For the number of employees, EUS-PLFS was used to derive the numbers for FY12 and FY18 (adjusted for private sector banks). The assumption is that the CPSEs mentioned above is not included in this set. Even if they are, the numbers we have derived above would lead to conservative values. The number of employees turn out to be 1.85 cr in FY12 and 2.33 cr in FY18. 

Since there were a lot of assumptions involved to derive this, we have to look at some proxy data to validate the above.

1. There is an article by Alpha Invesco (Source: S22) which pegs the Employee Benefits of BSE 500 companies at INR 7.8 lakh crore in FY18 and INR 5.2 lakh crore in FY14 with number of employees of 57 lakhs in FY18. This would include some listed Government PSUs and Banks as well. But it does not include the other listed companies, unlisted public limited companies and private limited companies. Further, as per an article by R. Nagaraj et al. titled Four years after the Base-Year Revision: Taking stock of the debate surrounding India’s National Accounts Estimates dated February 2021 published by IGIDR, public limited companies contributed ~55% of the GVA of private corporate sector (excluding quasi corporations) while private limited companies contributed the rest. Applying the same logic as mentioned above, the total salary expenses of INR 12.8 lakh crore for private corporate sector as a whole looks fine. 
2. As per a recent article in Business Standard (Source: S23), total employee benefits for FY22 by listed private corporates was INR ~10 lakh crore (this would include Banks as well though). There were articles in CMIE (Source: S24) which mentioned that listed company employment was almost 1 crore and adjusted for Government employment it would be almost 90 lakhs. Now, the figure derived as per the method described above for Private Corporate sector was INR 18 lakh crore for FY22 which was for almost 3.24 crore employees. Considering the top 90 lakhs crore earn INR 10 lakh crore, it seems, if anything, conservative that the rest 2.34 crore people earn INR 8 lakh crore. 

• Step 6: If we sum up the details in Steps 1 to 5 above, the total number of employees would be 3.39 crores and 3.89 crores in FY12 and FY18 respectively. It should be noted that there would be some Casual employees who would be included in this. However, the quantum of wages paid to them on an aggregate level may not be that significant. On the other hand, we have not included those regular protected workers who would be working in Defence Sector (non-civilian). They may add another 15-20 lakhs personnel with a Salary expense of INR 1 lakh crore (Source: S31) and State PSEs for which I have not looked at the data. So, there would be some compensation effects here. Now, as per the ILO Research Brief (Source: S2), there were 3.5 cr workers who were in the regular protected category in FY12 and 4.4 cr in FY18. This means that out of the total regular protected workers, around 17 lakh workers and 46 lakh workers that did not come in the above computation. For these employees, we assume they earn the salaries of regular unprotected workers for the respective years since the balance employees who are left out is very small compared to Method 1.

The Pic below summarizes the results. As can be seen below, the gap between the numbers as per the NSSO survey and the actuals is ~40% in FY12 which substantially increases to ~80% in FY18. Further, on a per person basis, there seems to have been a growth of almost 9% in real terms while the PLFS data showed a dip of almost 15%. As mentioned above, the Salaries to GVA ratio used for FY18 was the same as FY12 (i.e., 31.7%). In case, we end up using the actual ratio observed in FY18 (i.e., 36.8%) and corroborated by ASI data, the increase will be from INR 16.7 lakh crore (in FY12 prices) to INR 18.2 lakh crore leading to a per capita increase of 18.4%.

     Pic 6

 

Method 3: Using NAS Data

The earlier method data used salary/ wages data directly from (i) Central, State Government and Central PSEs (non-financial), (ii) Data for banking sector, (iii) Using data for non-financial private corporate sector from RBI and extrapolating that data using NAS. For this method, we shall use the data available with NAS alone with some adjustments which is described below. 

• Step 1: Take out the Compensation to Employees (COE) for Private Corporate Sector and Public Sector from NAS (Source: S21). This comes to INR 19 lakh crore for FY12 and INR 40 lakh crore for FY18. 
• Step 2: Adjust the COEs for Private Corporate sector for quasi-corporations based on GVA of Private Corporates without quasi-corporations. Without quasi corporations, the GVA would reduce by around 23-24% for the Private Corporate Sector (Source: S32). This would lead to COE reducing to INR 17 lakh crore in FY12 and INR 35 lakh crore in FY18.
• Step 3: As per the definition of COE (Source: S33), Compensation of employees is the total remuneration in cash or in kind payable by employers to employees for the work done. Direct social transfers from employers to their employees or retired employees and their family, such as payments for sickness, educational grants and pensions that do not set up an independent fund, are also imputed to compensation of employees. Hence, we have to reduce the pension amounts paid in FY12 and FY18. Pension outlays are available for Union Government from Union Budgets and for State Governments from RBI (Source: S16). This would reduce the number arrived at in Step 2 to INR 15 lakh crore in FY12 and INR 31 lakh crore in FY18. However, the definition of earnings by PLFS seems to suggest that while bonus payment will be included, employers' contribution to PF, social security etc. will be excluded while the COE definition seems to include the same. This is typically 12% of basic pay and basic pay will be a sub-component within the total pay. For private sector employees, this may be around 5% of the total pay while for Government sector it may come close to 10%. So, there may be an overestimation of the salary costs per person by 5-10% due to definitional differences between the earnings as per PLFS and COE. However, there are some compensatory factors as would be mentioned in Step 5 below.   
• Step 4: Take out the number of employees working in Government Sector/ PSEs and Limited Companies from EUS 2011-12 and PLFS 2017-18. This comes to 5.1 crore employees in FY12 and 5.7 crore employees in FY18. This is quite higher than the Regular protected employees as per EUS-PLFS (3.6 crores for FY12 and 4.4 crores for FY18) because some of the employees in the Private Corporate sector and Government may be Regular unprotected employees or Casual Employees. 
• Step 5: Take out the wages per employee and adjust it for CPI inflation as well. This leads to wages per employee of INR 3 lakhs per year in FY12 and INR 3.8 lakhs per employee for FY18 (in FY11-12 prices). As mentioned in Step 4, the average per employee is after factoring all the employees (regular protected and unprotected and casual on private corporate sector and Government). However, considering the earnings of the unprotected regular employees and casual workers would be paid much lesser than the regular protected employees, the average would most likely be an underestimate. This would at least partially compensate the overestimate on account of the different definitions of earnings under PLFS and COE as mentioned in Step 3 above.
• Step 6: Multiply the number of employees in the as per ILO who are protected regular wage earners. This would lead to the following pic. 

    Pic 7

 

As can be seen above, the gap between the numbers as per the NSSO survey and the actuals is ~19% in FY12 which substantially increases to ~83% in FY18. Further, on a per person basis, there seems to have been a growth of almost 29% in real terms while the PLFS data showed a dip of almost 15%. 

If we compare all the Methods, Method 1 and Method 3 yield very similar results for FY12 while all methods yield similar results for FY18. Considering Method 1 and Method 3 using 2 different sources of data give similar results for both Method 1 and Method 3, it is quite reasonable to assume that the incomes of Regular Employees on a person basis would have increased by around 25-30% in Real Terms and accordingly, so would the consumption spending of the Top Decile. 

Comparison of results (as % of PFCE)

While the point of the article was to re calculate for FY12 and FY18 only, the trend analysis shows that, if we substitute FY12 and FY18 with the actual data under the various methods, the fall as a percentage of PFCE from FY12 to FY18 is 0.9% in Method 1, 4.5% in Method 2 (this will reduce to around 2.5% if we remove the conservative assumption used to arrive at the numbers as described above) and 2.2% in Method 3. This is much lesser than the 8% fall observed as per NSSO data from FY12 to FY18. Further, as a % of PFCE, all three methods yield substantially yield higher results compared to the numbers derived using NSSO data. So, as per this, if the trend was correctly followed, ideally PLFS FY18 would have showed earnings as % of PFCE at around 30% which is in line with the trends of earlier years as well. 

    Pic 8

Sources: Data from MOSPI, Author's calculations

Some Consumption Indicators

Since incomes and consumption go hand-in-hand, any increase in incomes would lead to increase in consumption. Hence, the growth in the consumption of the top decile would also have been commensurate with increase in incomes. Further, we can see some other data to show that consumption indeed increased from FY12 to FY18 for the top decline. Here, we shall look at those parameters which will be largely used by the top decile of the population.

• Passenger Vehicle Sales increased from 2.6 mn in FY23 to 3.3 mn in FY18 (Source: S25).
• Domestic Airline passenger traffic almost doubled from 116 mn in FY13 to 243 mn in FY18 (Source: S26).
• AC sales increased from almost 3 mn in FY12 to almost 6 mn in FY18 (Source: S27).

Implications

There have been some recent criticisms of the NSSO data from the Government quarters itself, led by some of the members of the Prime Minister’s Economic Advisory Council (PM EAC) (Source: S28). The main argument was that the NSSO surveys underestimated the progress achieved by the country especially since 2011. They mainly relied on the fact that proportion of rural population is over-stated in the NSSO surveys vis-à-vis actual data (based on other estimates) thus leading to an underestimation in the progress achieved. Another criticism levelled by members of PM EAC pertains towards underestimation of the female labour force participation rates due to some issues with the survey questionnaire (Source: S29). Neither have I studied nor am I competent enough to weigh in on these issues.

Nevertheless, this article gives some more credence to the arguments made by the members of PM EAC. It seems that the ability to capture the top decile by the NSSO has further declined from FY12 to FY18 and it has led to incorrect results. 

So, any studies which uses the PLFS surveys may lead to wrong conclusions. Some examples as listed below: 

• The State of Inequality in India report by IFC (Source: S30): Based on the PLFS data it said that the only 10% of the population earned more than INR 25,000 per month. 
• Collapse in Wage/Salary Income Growth in India, 2011-12 to 2017-18 by Ravi Srivastava et al.: It says "A comparison of the growth rate of wages and salaries in India over two time periods (2004-05 to 2011-12 and 2011-12 to 2017-18 shows that wage growth virtually collapsed in the second period. Surprisingly, this collapse was even more dramatic among regular workers and in urban areas and in the higher deciles of wage/salary earners. These results show that the manifestations of the economic crisis were already quite widespread and were not only restricted to the informal sector or to the urban/rural poor. The results also confirm other results and analyses which have also suggested that genesis of the economic crisis and slow down which is currently being debated goes back several years and is related to a series of economic policy shocks since the early years of the last decade, which intensified after demonetization and subsequent policy shocks." There are a few interesting additional points in this study. First, the growth in earnings of Regular Wage wage earners (who would contribute the bulk of the earners in organized sector i.e., Government and Private Corporate sector) is negative. This has been shown to be wrong in this article. As an aside, if we look at the weighted average growth for casual workers, it seems to suggest that casual workers are mostly concentrated in unorganized sector since the weighted average almost matches with "Others" in Pic 9. Further, as per the same study, decile-wise income growths also show that for the bottom 50% there has been real growth in wages but it starts turning negative for regular wage earners from the 60th percentile onwards somewhat similar (but not wholly similar) to the consumption patterns as per CES from FY12 to FY18. This article's rebuttal is largely towards the trend for the top decile and I am not going into the income growth for the other deciles.          

           Pic 9
        
            Source: S34

        Pic 10

  

    Source: S34

The final question is why does a 6 year old data set matter now. Well, the sad part is that the main problems highlighted in this article is getting carried forward in the PLFS surveys conducted even today (refer Pic 11 below). The only saving grace is that the fall observed from FY12 to FY18 has not been observed since. So, at least the trend since FY18 is getting captured more or less correctly in PLFS. 

    Pic 11

One can only hope the CES conducted for FY22-23 was able to do the sampling better.

Sources

S1: Report of the Committee on Private Final Consumption Expenditure: https://www.mospi.gov.in/sites/default/files/publication_reports/Adhikari_Committee_PFCE_22may15.pdf

S2: ILO Research Brief, Employment, Labour Force and the Working Population in India 2000-2019: https://www.ilo.org/wcmsp5/groups/public/---asia/---ro-bangkok/---sro-new_delhi/documents/publication/wcms_775940.pdf

S3: Household Consumption of Various Goods and Services in India, 2017-18 – Leaked report

S4: Household Consumption of Various Goods and Services in India, 2011-12

S5: PLFS Annual Report, FY18 

S6: Employment-Unemployment survey, 2011-12

S7: Indian income inequality, 1922-2015: From British Raj to Billionaire Raj? By Thomas Piketty and Lucas Chancel, https://wid.world/document/chancelpiketty2017widworld/

S8: Black Money, White Paper: https://dor.gov.in/sites/default/files/FinalBlackMoney.pdf

S9: https://indianrailways.gov.in/railwayboard/uploads/directorate/stat_econ/IRSB_2012-13/PDF/Year_Book_Eng/5.pdf

S10: https://pib.gov.in/newsite/PrintRelease.aspx?relid=132774

S11: https://www.legallyindia.com/the-bench-and-the-bar/rti-reveals-number-of-lawyers-india-20130218-3448

S12: https://www.livemint.com/Companies/70e1RjLujR3SRRDTFagzhL/Hyundai-sees-lower-India-sales-in-2013.html

S13: https://incometaxindia.gov.in/Pages/Direct-Taxes-Data.aspx

S14: https://labourbureau.gov.in/uploads/pdf/First_QES_2021.pdf

S15: https://doe.gov.in/annual-report-pay-and-allowances

S16: 

https://rbi.org.in/Scripts/AnnualPublications.aspx?head=State%20Finances%20:%20A%20Study%20of%20Budgets

S17: https://www.satp.org/satporgtp/countries/india/database/State_Government_Employees_in_India.pdf

S18: https://dpe.gov.in/en/publication/pe-survey/pe-survey-report

S19: 

https://rbi.org.in/scripts/AnnualPublications.aspx?head=Trend+and+Progress+of+Banking+in+India

S20: 

https://www.rbi.org.in/Scripts/AnnualPublications.aspx?head=Handbook%20of%20Statistics%20on%20Indian%20Economy

S21: https://www.mospi.gov.in/publication/national-accounts-statistics-2023

S22: https://www.alphainvesco.com/blog/bse-500-employee-cost-employee-count/

S23: https://www.business-standard.com/industry/news/wage-bill-of-listed-pvt-companies-up-17-at-rs-11-5-trn-in-fy23-repor-123071700209_1.html

S24: https://economictimes.indiatimes.com/news/economy/indicators/listed-companies-employed-record-10-million-in-2021-22-cmie/articleshow/96248856.cms

S25: https://www.siam.in/cpage.aspx?mpgid=42&pgidtrail=89

S26: https://www.aai.aero/en/business-opportunities/aai-traffic-news

S27: https://www.nuvamawealth.com/insight/chart-of-the-day-2/indian-room-air-conditioner-market-witnessing-healthy-surge-in-volume-f71f1f

S28: https://indianexpress.com/article/opinion/columns/shamika-ravi-writes-our-national-surveys-are-based-on-faulty-sampling-8799300/

S29: https://twitter.com/sanjeevsanyal/status/1626794171108581378/photo/1

S30: 

https://competitiveness.in/wp-content/uploads/2022/05/Report_on_State_of_Inequality-in_India_Web_Version.pdf

S31: Annual Survey of Industries

S32: Changes In Methodology And Data Sources In The New Series Of National Accounts dated June 2015 published by MOSPI

S33: https://mospi.gov.in/sites/default/files/publication_reports/national_accounta_0.pdf

S34: Collapse in Wage/Salary Income Growth in India, 2011-12 to 2017-18 by Ravi Srivastava and Balakrushna Padhi from Institute for Human Development