Unravelling RBI’s 'Unemployment' Houdini Act

The latest release of KLEMS database by the RBI, which estimates a detailed break up of India’s Gross Domestic Product into contributions of factors of production, has triggered a wide debate on the employment situation. KLEMS stands for capital (K), labour (L), energy (E), materials (M) and service (S). Amid the high unemployment rate estimated at 9.2% by Centre for Monitoring Indian Economy, the RBI’s report does a Houdini act of not just making joblessness vanish but positing an employment explosion. 

As per RBI, at 643 million jobs in FY’24, India added 168 million since FY’18, implying that over a fourth of the total were added in just six years – higher than the additions in the previous 33 years since 1985.

With this, the workforce grew by 5.2%, significantly outpacing the 0.34% average during the previous 10 years, and the working-age population by 1.1%, thereby reversing the FY’11-FY’18 decline in employment/working-age population ratio to reach a peak of 71.2% in FY’24. Such an employment explosion is unprecedented, unmatched even by the post-pandemic surge in the US. 

If RBI’s claims of improving employment quality and productivity are true it should result in a) an extremely tight labour market, b) skyrocketing wages and household incomes, and c) a considerable surge in spending and savings. 

But since the real consumption expenditure has slowed sharply to 3.5-4% growth over the recent years and the household savings rate has declined to a 12-year low of 18.4% of GDP, it is appropriate to critically examine RBI’s claims of employment explosion. 

KLEMS data has multiple abnormalities

We start by highlighting some critical observations on the KLEMS data:

• The primary disconnect arises from the fact that while RBI KLEMS shows exuberant job creation since FY’18, real Gross Value Added growth decelerated sharply to 4.2% 5-year CAGR from 7% during FY’13-FY’18. 
• ASUSE data for the informal sectors shows contraction in real value added over the past seven years which intensifies the disconnect with the employment boom as per KLEMS.  
• RBI KLEMS estimates employment numbers as a product of reported worker-population ratio (WPR) as per PLFS data and extrapolated India’s population from the last census (2011), which is outdated and hence can be exposed to significant estimation risk. 
• The 643 million employment in FY24 implies a peak WPR of 46.2%, surging from a low of 36.1% in FY18, reversing the decline from 42% in FY05 and breaching the levels in FY81 at 42% when the economy was more labor intensive. 

Long-term data shows a declining trend in WPR matching the progression of capital-deepening technology which intensified since FY’06, thereby reducing the employment elasticity and labor required per unit of capital. Since the private capital formation has been slowing since FY’12, employment creation consistently fell to negligible levels till FY’18 (five-year increment of 2.9 million). 

Hence, the sudden surge in WPR in the backdrop of rising digitisation and automation, numerous exogenous shocks including demonetisation (2016), GST-led dislocations (2017), NBFC crisis (2018), global trade war (2019), pandemic lockdown (2020-21), and the persistent slackness in private capex is an aberration.

What qualifies for productive and disguised unemployment? 

For emerging markets such as India, the primary factor driving relatively higher growth is the shift of labor from less productive primary sectors such as agriculture and associated rural services to urban and modern sectors, which aligns with structural transformation process. 

Conversely, disguised unemployment is characterised by rising dependence of employment on rural and agriculture signifying reversal of economic transformation resulting in decrease in labor productivity, real earnings, and household savings. 

Employment explosion is de facto disguised unemployment

The employment explosion since FY’18 as per KLEMS appears to be driven by disguised unemployment. We estimate and ascertain disguised unemployment by a) calculating counterfactual employment assuming a pre-demonetisation trend in capital deepening (FY’08-FY’16), and b) reflecting on the trends in labor productivity and real wages since FY’18. 

Following a trend decline in employment additions during FY06-FY18, the counterfactual trend indicates that employment would have fallen by 14mn during FY18-FY23 as against a rise of 122 million as per KLEMS.

Thus, out of a total employed population of 597 mn in FY23, 441 mn are estimated to be productively employed, leaving 156 mn as disguised unemployment or less productive work. (these estimates ignore disguised unemployment in FY16).

When this is combined with the reported unemployment of 18 million (3% of the labor force, PLFS), the total effective unemployment is 174 million, with an effective unemployment rate of 28% of the reported labour force. Further analysis shows that agriculture accounts for 72% of the projected disguised unemployment, followed by services (28%), construction (-12%), and manufacturing (12%). The negative gap in employment in construction despite the significant government capex in the infrastructure sector indicates declining labor intensity due to mechanisation.

According to the PLFS data (2023), the considerable increase in WPR is being driven by young cohorts, particularly women who have turned to agriculture, and male workers resorting to low-wage rural construction the share of employment in urban construction drop.

Also read: India Has 110 Million Informal Sector Workers, Govt Releases Data for the First Time in a Decade

Lower labour productivity and income confirm rising disguised unemployment

According to the 2018-23 KLEMS data, real value added per worker decreased by 0.4% (5-year compound annual growth rate or CAGR), the lowest since FY86. Interestingly KLEMS data also shows that the five-year CAGR of real worker income decelerated to 4.7% (FY’18-FY’23) and a 28-year low of 3.8% between FY’19 and FY’24, down from 8% in FY’09. Even more significantly, worker income/worker contracted by 1.6% CAGR (FY’19-24), the lowest since 1986.

Furthermore, there is a broad-based deceleration in labour quality reflecting education level. The labour quality index fell to 0.3% CAGR from 0.6% between 2008 and 2013. PLFS data reveals that, while educated workers up to primary school continue to climb, all other categories, from middle school education to post-graduation, are declining. The deterioration in labor quality appears to be the outcome of household income constraints impacting education investment, as also reflected in the Consumer Expenditure Survey (CES 2023). 

KLEMS results of contracting real wages are consistent with household income stress evidenced in other sources such as ASUSE, PLFS, CBDT, and a summary of corporate results.

Sas per PLFS 2022-23, the average monthly real wage in rural and urban areas for self-employed, casual, and regular workers is estimated at INR 13,467, with a 5-year CAGR decline of approximately 3% in real terms.

In the formal sector, the average real earnings of individual and HUF Income Tax filers decreased by 0.7% (5-year CAGR)

Non-finance companies excluding IT have seen a 6% gain in employee remuneration since FY20, implying no growth in real spending net of CPI inflation. If we assume even a minor increase in formal sector employment, real average salaries probably fell.

KLEMS also reveals the GDP aberrations

Growth in real worker income correlates closely with real private final consumption expenditure [2004-05 series] till 2014, with a correlation coefficient of 0.82 (FY’91–FY’14).

However, the updated GDP statistics (base year 2011-12) and downwardly revised India’s growth from 2006 to 2014 demonstrate a low correlation between worker income and consumption, particularly during FY’09-FY’16 when it turns negative (-0.91).

Thus, flipping of the long-term correlation between real worker income and real PFCE from positive to negative is blatantly contradictory.

The urgency of a policy face-lift was never so high

Far from the enormous increase in employment reported by the RBI’s KLEMS data, the resounding evidence of contraction in real labour productivity and wages shows that unusual surge in employment numbers is symptomatic of an unprecedented level of disguised unemployment.

With household income accounting for 78% of GDP facing headwinds, the strong headline GDP growth likely masks the underlying structural fragility. 

The discordances have possibly led to a misplaced policy strategy that overwhelmingly relied on supply-side strategy in the hopes of reviving the elusive private capex. 

There is an urgent need for a policy facelift in favour of a growth model based on jobs in services, as well as a progressive tax structure that stimulates demand. This can be accomplished by reducing reliance on indirect taxes, lowering taxes on necessities, and raising income tax brackets for low-income earners. Healthcare, tourism, education, transportation and logistics are some low hanging fruits in the employment intensive services sector. 

The consequent budgetary burden can be mitigated by raising taxes on the wealthiest, decreasing subsidies for the affluents, limiting corporate exemptions, and relying on public-sector enterprises.

Dhananjay Sinha is co-head of Equities and head of Research of Strategy and Economics at Systematix Group.