## Advancing India’s Structural Transformation and Catch-up to the Technology Frontier

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### Executive summary and context
- Real GDP growth in India has averaged over 6 percent since 2000.
- An estimated 415 million people were lifted out of multidimensional poverty since 2005.
- India is one of the world’s largest producers of cereals, milk, and pulses, one of the largest exporters of jewelry, and the largest exporter of generic drugs in the world.
- India is estimated to account for 40 percent of Global Capability Centers.
- India’s moon landing in August 2023 noted as evidence of potential in the space economy.

### Structural transformation: sectoral shifts and productivity
- Sectoral value added shifts (1980 to 2019):
  - Agriculture share fell from over 40 percent in 1980 to 15 percent in 2019.
  - Services’ share rose from just over 30 percent to over 55 percent.
  - Manufacturing and construction shares remained relatively constant.
- Employment distribution (2019):
  - Agriculture and allied sectors: over 42 percent of workers.
  - Services: about 34 percent of workers.
  - Construction: about 12 percent of workers.
- Productivity patterns:
  - In 2019/20, labor in manufacturing and services was over 4.5 times more productive than in agriculture.
  - Labor productivity in agriculture and construction has grown slower than in other sectors since 1980.
  - Construction is an important employer but exhibits low productivity and limited improvement since 1980.

### Catching up to the technological frontier — industry-level evidence (KLEMS)
- Data and measurement:
  - Preferred measure: change in relative labor productivity defined as value added (constant U.S. dollars at 2011 prices) per employee at the 2-digit industry level.
  - Frontier defined as the 90th percentile of labor productivity among advanced economies.
  - Alternative metrics used as robustness checks: PPP-adjusted labor productivity and TFP.
- Key industry results (1995–2019 unless stated):
  - Agriculture:
    - 1995: Indian agricultural worker productivity was 2.3 percent of the frontier.
    - 2019: increased to 2.9 percent of the frontier.
    - PPP-adjusted labor productivity: 12.2 percent of the median productivity in advanced economies.
    - PPP-adjusted labor productivity: 42.6 percent of the median productivity in emerging markets.
    - PPP-adjusted labor productivity: 54.3 percent of the median productivity in Latin America and the Caribbean.
    - PPP-adjusted labor productivity: 84.4 percent of the median productivity in emerging and developing Asia.
  - Business services:
    - Employment increased by 13 million (from 1.6 million in 1995 to 14 million in 2019).
    - Narrowed distance to frontier by 9 percentage points.
    - Labor productivity at 18 percent of the frontier in 2019.
  - Mining and petroleum refining, information and business services, health, and other services: faster catch up observed.
  - Manufacturing sub-sectors with weak catch-up: wood and paper, chemicals, electrical and optical equipment, other manufacturing.
  - Machinery manufacturing regressed by 2 percentage points in distance to the labor productivity frontier.
  - Construction improved marginally; trade showed limited catch up.

### Catching up to the technological frontier — firm-level evidence (ORBIS)
- Sample and scope:
  - Final sample: 731,916 firms, of which 2,071 are Indian.
  - Firms included: firms with sales and employment data at some point in past 5 years; firms with more than 20 employees; firms with non-negative sales.
  - Industries analyzed: 109 industries with at least 5 Indian firms.
- Sales per employee (thousands of U.S. dollars; summary statistics):
  - 5th Percentile: Sales 490.0; Employees 21.0; Sales per Employee 9.8
  - 10th Percentile: Sales 946.3; Employees 23.0; Sales per Employee 19.6
  - 25th Percentile: Sales 2,710.0; Employees 32.0; Sales per Employee 50.0
  - Median: Sales 8,752.4; Employees 60.0; Sales per Employee 137.6
  - Mean: Sales 155,788.7; Employees 504.8; Sales per Employee 447.0
  - 75th Percentile: Sales 33,900.0; Employees 162.6; Sales per Employee 274.4
  - 90th Percentile: Sales 134,334.8; Employees 530.5; Sales per Employee 622.3
  - 95th Percentile: Sales 333,564.3; Employees 1,178.6; Sales per Employee 1,035.8
  - Standard Deviation: Sales 2,217,519; Employees 6,553; Sales per Employee 6,558
  - Number of observations: 731,916
- Findings on Indian firms:
  - Median Indian firm productivity averages 17 percent of sales per employee by frontier firms across industries.
  - 126 Indian firms operate at or above the technological frontier (95th percentile of non-Indian firms).
    - 12 are in computer programming or other information technology services.
    - 7 are in jewelry manufacturing.
  - Frontier Indian firms tend to be large:
    - Three quarters of Indian firms operating at the frontier have assets greater than $100 million.
    - 10 percent of Indian firms at the frontier are foreign owned versus 7 percent for non-frontier Indian firms.

### Employment needs, scenarios, and growth impact
- Labor force and population baseline (2022):
  - Working age population (15 years and older): just over 1 billion.
  - Labor force participation rate in 2022: 53 percent.
  - Unemployment rate in 2022: 5.7 percent (weekly status aggregation).
  - Unemployment rate based on usual status: 3.6 percent.
- UN projections:
  - Working age population: 1,169 million in 2030; 1,337 million in 2050.
- Jobs needed estimates (2023–2050):
  - Lower bound (2022): assume India at full employment at 2022 unemployment rate.
  - Upper bound (2022): assume LFPR of 60 percent; under this, estimate 80 million missing jobs in 2022.
  - 2030 estimates (UN population 1,169 million; unemployment 5.7 percent):
    - Lower bound jobs needed: 60 million.
    - Upper bound jobs needed: 148 million.
  - 2050 estimates (UN population 1,337 million; unemployment 5.7 percent):
    - Lower bound jobs needed: 83 million.
    - Upper bound jobs needed: 96 million.
  - Cumulative totals 2022–2050:
    - Lower bound: 143 million jobs.
    - Upper bound: 324 million jobs.
  - Alternative projection (National Commission on Population): range of 101 to 193 million jobs needed between 2020-2036 (excludes 32 million COVID-19 missing jobs in 2020).
- Annual job creation scenarios:
  - If LFPR rises as assumed, 11.6 million jobs per year between 2022 and 2050 would be needed.
  - If LFPR is constant, about 5 million jobs per year implied (60 million by 2030; 143 million by 2050).
  - Historical context: India created 12 million jobs annually on average between 2012-23; GDP growth averaged around 6 percent in that period.
- Counterfactual growth rebalancing (relative to 2010-19 baseline):
  - Baseline average growth (2010-19): 6.2 percent with contributions:
    - Employment: 1.1 percentage points.
    - Labor quality: 0.2 percentage points.
    - Capital stock: 3.8 percentage points.
    - Capital composition: 0.4 percentage points.
    - TFP: 0.7 percentage points.
  - Scenario 1 (5 percent of workforce shifts from agriculture to construction and ten services sub-sectors; total workers fixed): policies shifting labor out of agriculture boost growth by 0.2-0.5 percentage points.
  - Scenario 2 (5 percent of workforce shifts from agriculture to construction and services): growth increases modestly to 6.3 percent (text).
  - Scenario 3 (5 percent shift from agriculture to manufacturing): growth rises further to 6.7 percent (text); chart labels also report Scenario 3 as 6.8 percent — both figures are reported as they appear in the source.
  - Caveats: Scenarios assume no increase in unemployment; capital, labor quality, and TFP remain constant; no endogenous TFP impacts from labor shifting.

### Major empirical findings and key statistics
- Up to an additional 324 million jobs needed by 2050 (estimate excludes underemployment).
- Education and skill metrics:
  - 61 percent of the population aged 25 and older have at least completed primary education.
  - Comparative baselines: 71 percent among lower-middle income peers; 89 percent among upper middle-income countries.
  - Share with completed primary education: increased from 51.4 percent in 2011 to 61.4 percent in 2020.
  - Share with completed secondary education: rose from 26.9 percent to 31.7 percent between 2011 and 2020.
  - Skill mismatch (PLFS 2021/22 using ILO methodology):
    - Three quarters of India’s skilled agricultural workers have fewer years of formal education than desirable.
    - Over 60 percent of craft and related workers and plant and machine operators and assemblers have too few years of formal schooling.
    - 52 percent of services and sales workers have too few years of formal schooling.
    - Pockets of overeducation for clerks and technicians in Chandigarh, Puduchery, Andaman & N. Island, Haryana, and Delhi.
- Skilling and training capacity:
  - Industrial Training Institutes (ITIs) combined annual enrollment: 1.24 million students.
  - Apprenticeship trainees: 740 thousand.
- Production-Linked Incentive schemes (PLIs):
  - Multiyear cost assuming full implementation: 0.72 percent of FY 2022/23 GDP.
  - Authorities estimate PLIs may help create up to 6 million jobs.
  - Policy guidance: PLIs should be time bound, subject to rigorous cost-benefit analysis, and ensure competition is fostered.
- Central government public investment (net acquisition of nonfinancial assets as percent of GDP):
  - 2018/19: 1.6
  - 2019/20: 1.7
  - 2020/21: 2.1
  - 2021/22: 2.5
  - 2022/23: 2.7
  - 2023/24(P): 3.3

### Policy recommendations to advance structural transformation
- Strengthen education and skilling:
  - Continue investments to raise years of formal education and improve education quality.
  - Expand industry-centric, technologically-equipped skilling (ITIs, TVET integration, apprenticeships, industry-aligned short courses).
  - Use digital platforms (Skill India Digital) and design courses for coding, AI, robotics, mechatronics, IOT, 3D printing, and drones.
  - Facilitate migration to address regional skill mismatches.
- Advance labor market reforms:
  - Complete implementation of the four new federal labor codes and work with states to notify rules.
  - Increase labor market flexibility while maintaining adequate worker protection.
  - Loosen restrictive employment protection legislation cautiously to increase total employment, including female employment.
- Foster trade integration:
  - Remove tariff and non-tariff import and export restrictions to expose producers to competition and help them move closer to the technological frontier.
  - Negotiate and implement bilateral trade agreements to open markets for Indian exports.
- Remove red tape and obstacles to private sector growth:
  - Continue digitalization efforts (e.g., Udyam Portal) to streamline MSME registration.
  - Use PLIs cautiously: targeted, temporary, time bound, subject to cost-benefit analysis, and accompanied by broader market reforms.
- Facilitate access to credit:
  - Channel credit to the most productive firms and sectors.
  - Maintain vigilant supervision to ensure healthy credit growth and support private investment.
  - Facilitate exit of non-viable firms and promote asset resolution.
- Continue public investment push:
  - Strengthen physical public infrastructure and leverage digital public infrastructure to raise private sector productivity and lower logistics costs.
- Strengthen social safety nets:
  - More flexible and targeted safety nets can support rural-to-urban migration and structural transformation (example cited: “One Nation, One Ration Card” rollout during COVID-19).

### Conclusion — synthesis of findings
- India has achieved strong growth and poverty reduction but remains in mid-transformation from a rural-based to a services-led and industrializing economy.
- Productivity progress is limited in several key industries (agriculture, construction, trade) while some services sectors performed relatively better.
- Frontier performance is driven by a small set of cutting-edge firms; frontier firms are typically larger and somewhat more likely to be foreign-owned.
- Policies that shift labor toward higher-productivity sectors could raise GDP growth by 0.2-0.5 percentage points.
- Realizing gains from the demographic dividend requires wide-ranging structural reforms across education and skilling, labor markets, trade integration, business climate, credit access, public investment, and social safety nets.

*Source: IMF Working Paper — Advancing India’s Structural Transformation and Catch-up to the Technology Frontier (wpiea2024138-print-pdf).*

### EXECUTIVE SUMMARY _______________________________________________________________ 6

### EXECUTIVE SUMMARY

### Introduction and context
- Real GDP growth in India has averaged over 6 percent since 2000.
- This growth led to higher living standards and a sharp drop in multidimensional poverty.
- India is one of the world’s largest producers of cereals, milk, and pulses, and has become one of the largest exporters of jewelry and the largest exporter of generic drugs in the world.
- India is estimated to account for 40 percent of Global Capability Centers.
- India’s moon landing in August 2023 is noted as evidence of potential in the space economy.

### Structural transformation: sectoral shifts and productivity
- Agriculture’s share of aggregate output fell from over 40 percent in 1980 to 15 percent in 2019.
- Agriculture still accounted for 42 percent of workers in 2019, resulting in depressed labor productivity in the sector.
- Economic activity shifted mainly to services; construction became an important employer but exhibits low productivity and limited improvement since 1980.
- Overall, services outperformed manufacturing in catch-up to the technological frontier.

### Catching up to the technological frontier — industry-level evidence (KLEMS)
- Industry-level analysis used KLEMS data on output, inputs, and value added to compare Indian industries with advanced economies.
- Catch-up to the technological frontier was limited in:
  - Agriculture (which freed workers over the period)
  - Construction and trade (where employment rose the most)
- Business services:
  - Employment increased by 13 million workers.
  - The industry narrowed the distance to the technological frontier by 9 percentage points.

### Catching up to the technological frontier — firm-level evidence (ORBIS)
- Firm-level analysis used ORBIS financial metrics.
- Indian firms tend to have low productivity on average, but some firms already operate at the technological frontier.
- Frontier firms are typically larger (by assets or revenues).
- Frontier firms are especially prevalent in:
  - Computer programming
  - Other information technology services
  - Jewelry manufacturing

### Employment needs and impact on growth
- Estimated job creation needs for India by 2050: between 143-324 million jobs.
  - This estimate includes missing jobs as of 2022 and the increase in working age population by 2050.
  - The estimate does not include additional job needs due to current underemployment or explicitly account for non-farm jobs needed to shift workers from agriculture as the economy develops.
- A relatively small shift of employment away from agriculture into either construction and services (the existing trend) or manufacturing can boost GDP growth by 0.2-0.5 percentage points.

### Policy recommendations to advance structural transformation
- Continue the public investment push.
- Strengthen education and skilling.
- Advance labor market reforms.
- Foster trade integration.
- Remove red tape and other obstacles to private sector growth.
- Strengthen the social safety net.
- Facilitate access to credit.

*Source: EXECUTIVE SUMMARY, IMF Working Paper — Advancing India’s Structural Transformation and Catch-up to the Technology Frontier (wpiea2024138-print-pdf).*

### Introduction

### Introduction

### Growth and Employment Patterns
- Real GDP growth has averaged over 6 percent since 2000.
- An estimated 415 million people were lifted out of multidimensional poverty since 2005.
- Sectoral shifts since 1980:
  - Agriculture’s share of value added declined from over 40 percent in 1980 to 15 percent in 2019.
  - Services’ share of value added grew from just over 30 percent to over 55 percent.
  - Shares of value added in manufacturing and construction have been relatively constant over this period.
- Employment distribution:
  - Over 42 percent of workers are classified as working in agriculture and allied sectors.
  - The share of workers in services has risen to about 34 percent since 1980.
  - Construction employed about 12 percent of workers in 2019.
- Labor market characteristics:
  - Construction employment is largely low-skill, largely casual workers, similar to agriculture, with significant worker movement between these sectors, especially in rural areas.
  - Employment in manufacturing has increased minimally over time.

### Sectoral Productivity and Labor Reallocation
- Labor productivity trends:
  - Labor productivity in agriculture and construction has grown slower than in other sectors since 1980.
  - In 2019/20, labor in manufacturing and services was over 4.5 times more productive than in agriculture.
- Implication:
  - With low productivity workers in agriculture and construction making up over half the workforce, there is significant potential to boost growth via productivity-enhancing reforms that free workers to move to more productive sectors, raising wages as productivity rises.

### Growth Decomposition and Drivers
- Using India KLEMS and a production function growth decomposition:
  - Value added growth shifted from being labor driven in the 1980s towards more physical capital and TFP driven in more recent decades.
  - Capital and TFP have become more important in the services sector in particular.
- Historical policy links:
  - Shifts linked to pro-business reforms in the 1980s, market reforms in the early 1990s, liberalization, increases in FDI, and rapid services growth.
- Sectoral specifics:
  - Services are the main driver of value added but have not generated enough formal, high-productivity jobs to fully employ the working age population.
  - Construction growth has been largely driven by employment shifts with little productivity benefit.

### Catching up to the Technological Frontier: Methodology
- Data sources and coverage:
  - India KLEMS (Reserve Bank of India) and EU KLEMS (Luiss Lab) at the 2-digit industry level.
  - RBI KLEMS extends from 1980/81 to 2020/21 (financial year runs April to March).
  - EU KLEMS includes 27 EU member states, the US, Japan, and the United Kingdom, running from 1995 to 2020; covers 30 advanced economies with an unbalanced panel.
  - Focus period: 1995 to 2019 (1995/96 to 2019/20 for Indian data); the most recent observation (first COVID-19 year) is disregarded.
  - 25 industries mapped across databases; government excluded to focus on marketplace productivity.
- Preferred measure:
  - Change in relative labor productivity, defined as value added (constant U.S. dollars at 2011 prices) per employee.
  - Technological frontier defined as the 90th percentile of labor productivity among advanced economies for each industry and time.
- Alternative measures considered:
  - PPP-adjusted labor productivity:
    - Uses relative prices for 2005 at the industry level from Inklaar and Timmer (2014).
    - Formula presented to compute value added in PPP-adjusted U.S. dollars at 2005 prices.
    - PPP-adjusted measures control for the Penn-effect but rely on 2005 relative price estimates and require extrapolation of industry-specific deflators; India lacks producer price indexes for some services, making these results a robustness check rather than baseline.
  - Total Factor Productivity (TFP):
    - TFP for industry i at time t in country c defined as residual: TFP_i,t,c = Y_i,t,c / (L_i,t,c^alpha_i,t,c K_i,t,c^(1-alpha_i,t,c)), where alpha is average labor compensation share of value added between t−1 and t.
    - TFP abstracts from productivity increases induced by higher capital accumulation but requires stronger assumptions and more data, restricting countries available for frontier definition; used as robustness check.

### Results
- Uneven catch up to the technological frontier across industries:
  - Agriculture remained at very low relative productivity:
    - In 1995, Indian agricultural worker productivity was 2.3 percent of the frontier.
    - By 2019, it increased to only 2.9 percent.
    - Agriculture acts as a safety net; excess labor allocation keeps productivity depressed.
  - Manufacturing industries with weak catch-up: wood and paper, chemicals, electrical and optical equipment, and other manufacturing.
  - Machinery manufacturing regressed by 2 percentage points in distance to the labor productivity frontier over the period.
  - Construction improved marginally.
  - Faster catch up observed in mining and petroleum refining, information and business services, health, and other services.
  - Business services: labor productivity at 18 percent of the frontier in 2019.
- Employment shifts (1995–2019):
  - Employment in agriculture declined by 17 million.
  - Employment grew most in construction (+46 million) and trade (+33 million), both relatively low productivity industries with limited catch up to the frontier.
  - Manufacturing added only 15 million jobs (one tenth of net job creation).
  - Business services increased employment by 13 million (from 1.6 million in 1995 to 14 million in 2019) and narrowed distance to the frontier by 9 percentage points.
  - Industries with fast catch up such as mining, petroleum refining, and information services added relatively fewer jobs owing to low labor intensity.

### Robustness and Alternative Metrics
- Agriculture’s weak performance is consistent across metrics:
  - Catch up to the technological frontier in agriculture was 0.6 percentage points based on labor productivity (consistent with other measures).

*Source: wpiea2024138-print-pdf - Introduction*

### 0.5 percentage points when labor productivity is adjusted by PPP at the industry level,

### wpiea2024138-print-pdf - 0.5 percentage points when labor productivity is adjusted by PPP at the industry level,

### Sectoral catch-up to the technological frontier
- Agriculture
  - India’s PPP-adjusted labor productivity is 12.2 percent of the median productivity in advanced economies.
  - India’s PPP-adjusted labor productivity is 42.6 percent of the median productivity in emerging markets.
  - India’s labor productivity in agriculture is 54.3 percent of the median productivity in Latin America and the Caribbean.
  - India’s labor productivity in agriculture is 84.4 percent of the median productivity in emerging and developing Asia.
  - Conclusion: India’s agricultural sector has substantial room to catch up even relative to closer peers.
- Mining
  - Catch up to the frontier in labor productivity: 8.6 percentage points.
  - TFP-based catch up: 6.7 percentage points.
  - PPP-adjusted labor productivity catch-up: declines to 4.5 percentage points (reflecting convergence with international prices).
- Manufacturing
  - Limited increases in labor productivity mostly explained by higher capital accumulation.
  - TFP-based catch up in manufacturing on average: 0.5 percentage points (negative or barely positive in most sub-sectors).
  - PPP adjustments matter notably for manufacturing of petroleum and of vehicles.
- Utilities
  - Catch up to the frontier larger when measured in PPP-adjusted productivity or in TFP, reflecting significant improvements beyond capital accumulation.
- Construction
  - Catch up to the frontier in construction is fairly stable and low across metrics.
- Services
  - Average catch-up in labor productivity: 6.3 percentage points.
  - Average TFP-based catch-up in services: 3.4 percentage points.
  - PPP-adjusted labor productivity suggests a much larger catch-up in services, but interpretation requires caution due to lack of producer price indexes for services in India (GDP deflator relies on other price data such as wholesale price indexes for goods).

### Figures and measurement notes
- Frontier definition
  - Country-level analysis: frontier defined as the 90th percentile among advanced economies.
  - Firm-level analysis: frontier defined as the 95th percentile of sales per employee across non-Indian firms by industry.
- Labor productivity definitions used
  - Labor productivity: value added (in constant U.S. dollars) per employee at the 2-digit industry level.
  - Labor productivity adjusted by PPP: value added in PPP-adjusted U.S. dollars at the industry level for the numerator.
  - TFP: total factor productivity computed as a residual.
- Data sources cited
  - Country authorities, EU KLEMS, World Development Indicators, World Economic Outlook, ORBIS, IMF staff estimates.

### Firm-level evidence (ORBIS-based)
- Sample and scope
  - Final sample: 731,916 firms, of which 2,071 are Indian.
  - Firms included: sales and employment data at some point in past 5 years; firms with more than 20 employees; firms with non-negative sales.
  - Industries analyzed: industries with at least 5 Indian firms, restricting the sample to 109 industries.
- Sales per employee (summary statistics, thousands of U.S. dollars)
  - 5th Percentile: Sales 490.0; Employees 21.0; Sales per Employee 9.8
  - 10th Percentile: Sales 946.3; Employees 23.0; Sales per Employee 19.6
  - 25th Percentile: Sales 2,710.0; Employees 32.0; Sales per Employee 50.0
  - Median: Sales 8,752.4; Employees 60.0; Sales per Employee 137.6
  - Mean: Sales 155,788.7; Employees 504.8; Sales per Employee 447.0
  - 75th Percentile: Sales 33,900.0; Employees 162.6; Sales per Employee 274.4
  - 90th Percentile: Sales 134,334.8; Employees 530.5; Sales per Employee 622.3
  - 95th Percentile: Sales 333,564.3; Employees 1,178.6; Sales per Employee 1,035.8
  - Standard Deviation: Sales 2,217,519; Employees 6,553; Sales per Employee 6,558
  - Number of observations: 731,916
- Findings on Indian firms
  - Median Indian firm productivity: averages 17 percent of sales per employee by frontier firms across industries.
  - 126 Indian firms operate at or above the technological frontier (95th percentile of non-Indian firms).
    - 12 of these are in computer programming or other information technology services.
    - 7 of these are in jewelry manufacturing.
  - Frontier Indian firms tend to be large:
    - Three quarters of Indian firms operating at the frontier have assets greater than $100 million.
    - 10 percent of Indian firms at the frontier are foreign owned versus 7 percent for non-frontier Indian firms.
  - Implication stated in text: success of frontier Indian firms stresses importance of removing obstacles preventing firms from growing and fostering foreign direct investment.

### Employment needs and growth impact
- Labor force and population baseline
  - Working age population (15 years and older) in 2022: just over 1 billion.
  - Labor force participation rate in 2022: 53 percent.
  - Unemployment rate in 2022: 5.7 percent (weekly status aggregation); unemployment rate based on usual status: 3.6 percent.
  - UN projection: working age population of 1,169 million in 2030; 1,337 million in 2050.
- Estimation approach for jobs needed (2023–2050)
  - Lower bound (2022): assume India at full employment at 2022 unemployment rate.
  - Upper bound (2022): assume labor force participation rate (LFPR) of 60 percent (LFPR in 2005 and approx. G20 emerging market average). Under this, estimate 80 million missing jobs in 2022.
  - 2030 estimates (UN working age population 1,169 million; unemployment rate 5.7 percent)
    - Lower bound jobs needed: 60 million.
    - Upper bound jobs needed: 148 million.
  - 2050 estimates (UN working age population 1,337 million; unemployment rate 5.7 percent)
    - Lower bound jobs needed: 83 million.
    - Upper bound jobs needed: 96 million.
  - Cumulative totals 2022–2050
    - Lower bound estimate of jobs needed: 143 million.
    - Upper bound estimate of jobs needed: 324 million.
  - Alternative population projections (National Commission on Population): using that methodology yields a range of 101 to 193 million jobs needed between 2020-2036 (note: excludes 32 million COVID-19 missing jobs in 2020).
- Counterfactual growth decomposition exercise
  - Baseline average growth (2010-19): growth rate 6.2 percent with contributions:
    - Employment: 1.1 percentage points.
    - Labor quality: 0.2 percentage points.
    - Capital stock: 3.8 percentage points.
    - Capital composition: 0.4 percentage points.
    - TFP: 0.7 percentage points.
  - Scenario 1: fix total number of workers; assume 5 percent of workforce shifts from agriculture to construction and ten services sub-sectors (equal proportions); assume all workers find jobs; replace agriculture workers by machinery in agriculture (value added does not decline, labor productivity rises); estimate impact on GVA using historical elasticity of GVA growth to employment growth (OLS, 2010-19) and compute new aggregate employment contribution using Tornquist aggregation.
  - Scenario 2: same as Scenario 1 but assume 5 percent of workforce shifts from agriculture to the 13 manufacturing sub-sectors.

### Policy-relevant observations highlighted in the text
- Many manufacturing productivity shortfalls appear driven by low TFP-based catch up, suggesting factors beyond capital accumulation constrain productivity.
- Frontier Indian firms are more likely to be larger and slightly more foreign-owned, consistent with literature that FDI can increase productivity.
- Text emphasizes importance of removing obstacles preventing firms from growing and fostering foreign direct investment.

*Source: https://www.imf.org/-/media/files/publications/wp/2024/english/wpiea2024138-print-pdf.pdf*

### 11.6 million jobs per year between 2022 and 2050). If we instead assume a constant LFPR – which would

### Advancing India’s Structural Transformation and Catch-up to the Technology Frontier

### Missing jobs and labor force projections
- If India maintains a rising labor force participation rate (LFPR), it would need to create 11.6 million jobs per year between 2022 and 2050.
- Under an alternative assumption of a constant LFPR, India would need to create:
  - 60 million jobs by 2030 (cumulative)
  - 143 million jobs by 2050 (cumulative)
  - This alternative implies about 5 million jobs per year.
- These estimates represent the total number of jobs to be created in the economy, not additional jobs above baseline job creation expected with economic growth.
- Historical context:
  - India created 12 million jobs annually on average between 2012-23.
  - India’s GDP growth averaged around 6 percent during that period.
- The estimate of missing jobs may be a lower bound once underemployment is considered; underemployment examples include:
  - Part-time workers desiring full-time work
  - Over-skilled workers for their current jobs
  - Those working in government job guarantee schemes (MNREGA)
  - Unpaid family labor
- Structural shifts imply demand for non-farm jobs:
  - Employment in unpaid family worker, own account workers, and casual workers is expected to decline as labor moves from farm to non-farm activities.
  - More regular wage jobs in urban areas will be needed to absorb this extra labor.
- Outward migration affects domestic job needs:
  - Greater-than-projected emigration would reduce domestic jobs needed; rising skilled migration and remittances already observed.

### Growth decomposition and counterfactual scenarios
- Growth decomposition (India vs. peers) summary:
  - Labor’s contribution to growth in India is small relative to other emerging market economies because of many missing and low-productivity jobs.
  - India’s recent growth has been more capital driven and driven by TFP, making it more comparable to advanced economies.
  - Supporting growth in large, productive sectors like manufacturing could absorb much of India’s labor and increase labor’s contribution to growth.
  - Stronger education and training would help boost labor quality contribution, as observed in other emerging markets.
- Counterfactual rebalancing exercise (relative to 2010-19 baseline):
  - Policies that shift labor out of agriculture boost growth by 0.2-0.5 percentage points.
  - Scenario 2 (5 percent of agricultural workforce shifts to construction and services):
    - Growth increases modestly to 6.3 percent.
    - Assumptions: no increase in unemployment; capital, labor quality, and TFP remain constant; no endogenous TFP impacts from labor shifting.
  - Scenario 3 (5 percent of agricultural workforce shifts to manufacturing):
    - Growth would rise further to 6.7 percent (manufacturing assumed more labor intensive and productive).
    - Same caveats on unemployment and TFP estimates apply.
  - Caveats on assumptions:
    - No assumed rise in unemployment may be optimistic during occupational transitions.
    - No assumed endogenous impact on TFP from labor shifts; actual TFP impact is ambiguous (could rise if workers join higher-productivity sectors or fall temporarily from skill mismatch).

### Major empirical findings and key statistics
- Overall job needs:
  - Up to an additional 324 million jobs needed by 2050 (estimate excludes underemployment).
- Education and skill metrics:
  - 61 percent of the population aged 25 and older have at least completed primary education.
  - Comparative baselines: 71 percent among lower-middle income peers; 89 percent among upper middle-income countries.
  - The share of India’s population aged 25 years or more who have at least completed primary education increased from 51.4 percent in 2011 to 61.4 percent in 2020.
  - The share with completed secondary education rose from 26.9 percent to 31.7 percent between 2011 and 2020.
  - Skill mismatch (PLFS 2021/22 using ILO methodology):
    - Three quarters of India’s skilled agricultural workers have fewer years of formal education than desirable.
    - Over 60 percent of craft and related workers and plant and machine operators and assemblers have too few years of formal schooling.
    - 52 percent of services and sales workers have too few years of formal schooling.
    - Pockets of overeducation exist for clerks and technicians, notably in Chandigarh, Puduchery, Andaman & N. Island, Haryana, and Delhi.
- Skilling and training programs:
  - Industrial Training Institutes (ITIs) combined annual enrollment: 1.24 million students.
  - Apprenticeship trainees: 740 thousand.
  - Skill India Digital platform and industry-aligned short-term training introduced; courses designed for coding, AI, robotics, mechatronics, IOT, 3D printing, and drones piloting and maintenance.
- Production-Linked Incentive schemes (PLIs):
  - Multiyear cost assuming full implementation: 0.72 percent of FY 2022/23 GDP.
  - Authorities estimate PLIs may help create up to 6 million jobs.
  - Policy guidance: PLIs should be subjected to rigorous cost-benefit analysis, be time bound, and ensure competition is fostered.
- Public investment:
  - Central government public investment (net acquisition of nonfinancial assets as percent of GDP):
    - 2018/19: 1.6
    - 2019/20: 1.7
    - 2020/21: 2.1
    - 2021/22: 2.5
    - 2022/23: 2.7
    - 2023/24(P): 3.3
  - Union government efforts expected to raise central public investment to 3.3 percent of GDP in 2023/24.
- Other numeric points:
  - Historical baseline growth in counterfactual chart: baseline 6.2 percent (2010-19 average referenced).
  - Scenario outcomes in chart: Baseline 6.2; Scenario 2 6.3; Scenario 3 6.8 (chart labels), while text describes Scenario 3 rising to 6.7 percent—both figures are reported as they appear in the source.

### Policy recommendations to advance structural transformation
- Strengthen education and skilling:
  - Continue investments to raise years of formal education and improve education quality.
  - Expand industry-centric, technologically-equipped skilling (ITIs, TVET integration, apprenticeships, industry-aligned short courses).
  - Use digital platforms (Skill India Digital) and design courses for emerging skill areas (coding, AI, robotics, mechatronics, IOT, 3D printing, drones).
  - Facilitate migration to address regional skill mismatches.
- Advance labor market reforms:
  - Complete implementation of the four new federal labor codes and work with states to notify rules.
  - Increase labor market flexibility while maintaining adequate worker protection.
  - Loosening restrictive employment protection legislation could increase total employment over time (including female employment), though short-term displacement risks exist.
- Foster trade integration:
  - Remove tariff and non-tariff import and export restrictions to expose producers to competition and help them move closer to the technological frontier.
  - Negotiate and implement bilateral trade agreements to open markets for Indian exports.
- Remove red tape and obstacles to private sector growth:
  - Continue digitalization efforts (e.g., Udyam Portal) to streamline MSME registration.
  - Use PLIs cautiously: targeted, temporary, time bound, subject to cost-benefit analysis, and accompanied by broader market reforms.
- Facilitate access to credit:
  - Channel credit to the most productive firms and sectors to foster growth and employment.
  - Maintain vigilant supervision to ensure healthy credit growth and support private investment.
  - Facilitate exit of non-viable firms and promote asset resolution.
- Continue public investment push:
  - Strengthen physical public infrastructure and leverage digital public infrastructure to raise private sector productivity and lower logistics costs.
- Strengthen social safety nets:
  - More flexible and targeted safety nets can support rural-to-urban migration and structural transformation (example: “One Nation, One Ration Card” rollout during COVID-19).

### Conclusion — synthesis of findings
- India has achieved strong growth and poverty reduction but remains in mid-transformation from a rural-based to a services-led and industrializing economy.
- Productivity progress is limited in several key industries (agriculture, construction, trade) while some services sectors performed relatively better; frontier performance is driven by a small set of cutting-edge firms.
- India may need up to an additional 324 million jobs by 2050 (excluding underemployment).
- Policies that shift labor toward higher-productivity sectors could raise GDP growth by 0.2-0.5 percentage points.
- Realizing gains from the demographic dividend requires wide-ranging structural reforms across education and skilling, labor markets, trade integration, business climate, credit access, public investment, and social safety nets.

*Source: IMF Working Paper — Advancing India’s Structural Transformation and Catch-up to the Technology Frontier*

### Annex I.  Mapping of Industries in KLEMS

### Annex I. Mapping of Industries in KLEMS

### Databases
- In this annex, we describe how we map industries across the two KLEMS databases.
- The first two columns of Table A1 show our industry names and codes. The last two columns show the specific industries in the RBI and EU KLEMS datasets that correspond to each of our industries.
- While acknowledging that the mapping is not perfect, a more precise mapping is not possible due to lack of more granular data and methodological differences.
- Example note: study industry “Other Services” includes “Real Estate Activities” in the RBI KLEMS database (RBI, 2023), but “Real estate activities” in the EU KLEMS incorporates imputed rents of owner-occupied dwellings, which the Indian data does not cover. Given the large size of this imputation, we decide to drop it from the analysis, even when we cannot drop the “Real Estate Activities” component from “Other Services” in the RBI KLEMS database.

### Table A1. Mapping of Industries Across KLEMS Databases — Code Level Mappings
- Code: A
  - Industry: Agriculture
  - RBI KLEMS Industries: Agriculture, Hunting, Forestry and Fishing
  - EU KLEMS Industries: Agriculture, forestry and fishing

- Code: B
  - Industry: Mining
  - RBI KLEMS Industries: Mining and Quarrying
  - EU KLEMS Industries: Mining and quarrying

- Code: C01
  - Industry: Food
  - RBI KLEMS Industries: Food Products, Beverages and Tobacco
  - EU KLEMS Industries: Manufacture of food products; beverages and tobacco products

- Code: C02
  - Industry: Textiles
  - RBI KLEMS Industries: Textiles, Textile Products, Leather and Footwear
  - EU KLEMS Industries: Manufacture of textiles, wearing apparel, leather and related products

- Code: C03
  - Industry: Wood
  - RBI KLEMS Industries: Wood and Products of wood
  - EU KLEMS Industries: Manufacture of wood, paper, printing and reproduction

- Code: C04
  - Industry: Petroleum
  - RBI KLEMS Industries: Coke, Refined Petroleum Products and Nuclear fuel
  - EU KLEMS Industries: Manufacture of coke and refined petroleum products

- Code: C05
  - Industry: Chemicals
  - RBI KLEMS Industries: Chemicals and Chemical Products
  - EU KLEMS Industries: Manufacture of chemicals and chemical products; Manufacture of basic pharmaceutical products and pharmaceutical preparations

- Code: C06
  - Industry: Rubber
  - RBI KLEMS Industries: Rubber and Plastic Products; Other Non-Metallic Mineral Products
  - EU KLEMS Industries: Manufacture of rubber and plastic products and other non-metallic mineral products

- Code: C07
  - Industry: Metals
  - RBI KLEMS Industries: Basic Metals and Fabricated Metal Products
  - EU KLEMS Industries: Manufacture of basic metals and fabricated metal products, except machinery and equipment

- Code: C08
  - Industry: Electrical
  - RBI KLEMS Industries: Electrical and Optical Equipment
  - EU KLEMS Industries: Manufacture of computer, electronic and optical products; Manufacture of electrical equipment

- Code: C09
  - Industry: Machinery
  - RBI KLEMS Industries: Machinery, nec.
  - EU KLEMS Industries: Manufacture of machinery and equipment n.e.c.

- Code: C10
  - Industry: Vehicles
  - RBI KLEMS Industries: Transport Equipment
  - EU KLEMS Industries: Manufacture of motor vehicles, trailers, semi-trailers and of other transport equipment

- Code: C11
  - Industry: Other Manufacturing
  - RBI KLEMS Industries: Manufacturing, nec; recycling
  - EU KLEMS Industries: Manufacture of furniture; jewellery, musical instruments, toys; repair and installation of machinery and equipment

- Code: D
  - Industry: Utilities
  - RBI KLEMS Industries: Electricity, Gas and Water Supply
  - EU KLEMS Industries: Electricity, gas, steam and air conditioning supply; Water supply; sewerage, waste management and remediation activities

- Code: F
  - Industry: Construction
  - RBI KLEMS Industries: Construction
  - EU KLEMS Industries: Construction

- Code: G
  - Industry: Trade
  - RBI KLEMS Industries: Trade
  - EU KLEMS Industries: Wholesale and retail trade; repair of motor vehicles and motorcycles

- Code: H
  - Industry: Transport
  - RBI KLEMS Industries: Transport and Storage
  - EU KLEMS Industries: Land transport and transport via pipelines; Water transport; Air transport; Warehousing and support activities for transportation

- Code: I
  - Industry: Hotels
  - RBI KLEMS Industries: Hotels and Restaurants
  - EU KLEMS Industries: Accommodation and food service activities

- Code: J
  - Industry: Information
  - RBI KLEMS Industries: Post and Telecommunication
  - EU KLEMS Industries: Postal and courier activities; Information and communication

- Code: K
  - Industry: Financial
  - RBI KLEMS Industries: Financial Services
  - EU KLEMS Industries: Financial and insurance activities

- Code: M
  - Industry: Business
  - RBI KLEMS Industries: Business Service
  - EU KLEMS Industries: Professional, scientific and technical activities; Administrative and support service activities

- Code: O
  - Industry: Government
  - RBI KLEMS Industries: Public Administration and Defense; Compulsory Social Security
  - EU KLEMS Industries: Public administration and defence; compulsory social security

- Code: P
  - Industry: Education
  - RBI KLEMS Industries: Education
  - EU KLEMS Industries: Education

- Code: Q
  - Industry: Health
  - RBI KLEMS Industries: Health and Social Work
  - EU KLEMS Industries: Human health and social work activities

- Code: R
  - Industry: Other Services
  - RBI KLEMS Industries: Other Services
  - EU KLEMS Industries: Arts, entertainment and recreation; Other service activities

*Source: IMF staff estimates.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2024/english/wpiea2024138-print-pdf.pdf_