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GS Paper: GS3-02.Inclusive growth and issues therein

  • Behind worker’s protest: High costs, stagnant wages

    Why in the News?

    Recent protests by factory workers in Noida, Ghaziabad and Manesar have brought attention to a sharp divergence between rising inflation and stagnant wages. CPI-IW (base year 2016) shows industrial worker inflation rising by 24.8% nationally (Feb 2021-Feb 2026), while key industrial clusters recorded even higher inflation: 27.9% in Gurugram, 27.2% in Faridabad, and ~27.4% in Ghaziabad, Noida, and Delhi. In contrast, minimum wages increased at a much slower pace, Haryana (~15%), Delhi (~20.6%), Uttar Pradesh (~24.6%). This widening gap has reduced real wages, triggering protests.

    Why are workers protesting despite periodic wage revisions?

    1. Real Wage Erosion: Indicates decline in purchasing power; inflation (24.8%) exceeded wage growth across states.
    2. Regional Inflation Spike: Shows concentrated distress; Gurugram (27.9%), Faridabad (27.2%), Noida/Delhi (~27.4%).
    3. Inadequate Wage Growth: Reflects disparity. In Haryana, wages saw a lower increase (~15%) compared to the ~27.9% inflation rate before the April 2026 revision. Similarly, in Uttar Pradesh, the 10-year wage increase (42%) is significantly lower than the cost of living increase, resulting in lower real wages compared to a decade ago.
    4. Cost of Living Pressures: Includes rent, LPG, food; example, workers report LPG cylinder costs exceeding ₹4,000 in informal markets.
    5. Expectation Gap: Indicates mismatch between announced revisions and actual income improvements.

    How has inflation outpaced wages structurally?

    Inflation has structurally outpaced wage growth in India by creating a persistent gap where rising living costs (food, rent, fuel) consistently exceed nominal salary adjustments, leading to a decline in real purchasing power. This phenomenon is driven by a failure in the wage-indexation mechanism, regional disparities in inflation, and a shift towards variable pay that does not match the rapid rise of essentials.

    1. CPI-IW Linkage Failure: Shows weak adjustment of wages with CPI-IW (base 2016).
      1. Weak Adjustment: Wage revisions, particularly in manufacturing, often lag behind CPI-IW movements, meaning workers feel the price rise long before they receive any compensation.
      2. Time Lag: The 6-monthly Variable Dearness Allowance (VDA) adjustment is often too slow during high-inflation periods, leaving workers vulnerable
    2. National vs Regional Gap: Demonstrates divergence; national inflation (24.8%) lower than industrial clusters (~27%).
    3. Nominal vs Real Wages: Indicates nominal increase but real decline.
      1. While nominal salaries have increased (often 8-10% annually), the “real wage” (purchasing power) has remained flat or declined because essential costs have risen faster.
    4. Multi-component Inflation: Includes housing, fuel, food simultaneously rising.
      1. Housing & Fuel: Fuel costs rise and feed into logistics and travel, increasing costs of goods. Rent in urban industrial areas also frequently spikes, placing pressure on lower income brackets.
      2. Food and Beverages: This category, taking a high weight in worker consumption, often witnesses high volatility and consistent upward pressure, hitting low-income households hardest
    5. Labour Bureau Data: Labour Bureau data highlights that corporate profits in many sectors (e.g., manufacturing/engineering) have grown much faster than wage shares.
      1. Wage-Share Decline: Between 2015 and 2023, corporate profits as a share of GDP rose from 3.8% to 5.2%, while the wage share declined.
      2. Productivity Gap: Indian workers are becoming more productive (higher output per worker), but these gains are translating into corporate profits rather than increased wage rates, resulting in a structural gap

    What are the new Labour Codes and what do they assure?

    1. Code on Wages, 2019: Ensures universal minimum wage and timely payment across sectors.
    2. Industrial Relations Code, 2020: Regulates hiring, firing, and dispute resolution mechanisms.
    3. Code on Social Security, 2020: Extends social protection to unorganised and gig workers.
    4. Occupational Safety, Health and Working Conditions Code, 2020: Ensures safety standards, working hours, and welfare provisions.
    5. Assurance Framework: Establishes 8-hour workday norm, 48-hour weekly cap, overtime compensation, and safe working conditions.

    What is happening in implementation on the ground?

    1. Delayed Notification: While effective from Nov 2025, not all state rules are fully notified or uniformly enforced, leading to partial implementation.
    2. Employer Discretion: The flexibility provided has seen reports of increased working hours (up to 12 hours/day) and worker complaints about non-payment or underpayment of overtime, particularly in manufacturing hubs.
    3. Worker Complaints: Highlights non-payment or underpayment of overtime in factories in Noida and Manesar.
    4. Administrative Gaps: Demonstrates lack of inspection and enforcement capacity.
      1. There is a notable lack of enforcement capacity, with a shift from “Inspector Raj” to an “Inspector-cum-Facilitator” system.
    5. Transition Uncertainty: Reflects confusion during shift from old laws to new codes.

    Why is there confusion around working hours and overtime?

    1. Definition Gaps: Shows ambiguity between “working hours” and “spread-over”; example-12-hour presence including breaks treated as normal shift in some factories.
    2. State-Level Rules: Indicates variation; example: different states interpreting overtime eligibility differently under draft rules.
    3. Spread-over Norms: Includes rest intervals within 12-hour cap; example: worker present for 12 hours but paid for 8 hours citing breaks.
    4. Overtime Ambiguity: Highlights unclear thresholds; example: workers exceeding 8 hours not always compensated at double rate.
    5. Inspection Challenges: Demonstrates weak monitoring; example: industrial clusters with limited labour inspections.

    What are the structural issues in wage determination?

    1. Irregular Revision Cycle: Shows failure of annual revision mechanism.
    2. State Disparity: Indicates uneven wage standards across Haryana, UP, Delhi.
    3. Categorisation Complexity: Includes multiple wage categories (skilled/unskilled).
    4. Pandemic Disruption: Highlights delayed revisions during Covid-19 period.
    5. Weak Enforcement: Demonstrates gaps in compliance monitoring.

    What are the broader economic implications?

    1. Demand Compression: Reduces consumption due to declining real incomes.
    2. Labour Unrest: Increases frequency of industrial protests.
    3. Productivity Impact: Affects industrial output in key clusters.
    4. Informalisation: Encourages off-the-books employment practices.
    5. Inequality Expansion: Widens gap between labour and capital incomes.

    Way Forward

    1. CPI-Linked Wage Indexation: Ensures automatic revision of minimum wages with CPI-IW; prevents real wage erosion amid 24-28% inflation trends.
    2. Clear Labour Code Rules: Defines working hours, overtime, and spread-over explicitly; removes ambiguity in 12-hour shift interpretation.
    3. Uniform National Floor Wage: Establishes enforceable baseline wage across states; reduces disparities such as Haryana vs Uttar Pradesh.
    4. Overtime Enforcement Mechanism: Ensures double wages beyond 8 hours; strengthens compliance in industrial clusters like Noida-Manesar.
    5. Strengthened Labour Inspection System: Deploys digital inspections and audits; improves enforcement and reduces informal labour practices.

    Conclusion

    The divergence between inflation and wage growth reflects structural inefficiencies in India’s labour economy. Strengthening CPI-linked wage revision, ensuring clarity in Labour Code rules, and improving enforcement mechanisms remain essential.

    PYQ Relevance

    [UPSC 2024] Discuss the merits and demerits of the four ‘Labour Codes’ in the context of labour market reforms in India. What has been the progress so far in this regard?

    Linkage: The PYQ directly aligns with the article’s focus on Labour Codes, especially issues of implementation, wage protection, and working-hour ambiguities. It extends the debate from policy intent (merits) to ground realities (demerits), including wage stagnation, enforcement gaps, and labour unrest.

  • Startup India Fund of Funds (FoF) 2.0  

    Why in the News?

    • Government notified Startup India FoF 2.0 (April 13, 2026) with a ₹10,000 crore corpus to boost startup funding.

    About FoF 2.0

    What it is

    • A government-backed Fund of Funds
    • Invests in: Alternative Investment Funds
    • These AIFs then invest in startups
      • Indirect funding mechanism (not direct investment)

    Institutional Framework

    • Nodal Department: Department for Promotion of Industry and Internal Trade
    • Implementation Agency: Small Industries Development Bank of India
    • Regulator for AIFs: Securities and Exchange Board of India

    Background

    • FoF 1.0 (2016) under Startup India Action Plan
    • FoF 2.0 builds on it with:
      • More focus on advanced technologies
      • Stronger capital mobilization
    [2025] With reference to investments, consider the following: 
    I. Bonds 
    II. Hedge Funds 
    III. Stocks
    IV. Venture Capital 
    How many of the above are treated as Alternative Investment Funds? 
    (a) Only one (b) Only two (Hedge Funds and Venture Capital) (c) Only three (d) All the four

  • AI’s impact on labour market: Anthropic’s report flags high exposure 

    Why in the News?

    Artificial Intelligence is increasingly reshaping labour markets worldwide. A recent report by Anthropic shows that jobs involving digital tasks, cognitive work, and routine analysis face higher automation risks due to large language models (LLMs). This shift has implications for skills, education, and employment policies, especially for countries like India, where millions work in IT, services, and BPO sectors.

    What does the Anthropic report reveal about AI exposure in labour markets?
    The Anthropic report marks one of the first systematic attempts to measure real-world labour market exposure to AI rather than relying only on theoretical predictions.

    1. New Measurement Metric- “Observed Exposure”: Introduces a framework combining LLM technical capabilities with real-world usage data from Claude AI systems, enabling more accurate estimation of AI’s impact on jobs.
    2. High Exposure in Digital Occupations: Identifies sectors such as business and finance, management, computer science, engineering, legal services, and office administration as highly exposed to AI-driven automation.
    3. Striking Capability Statistic: Finds that LLMs are theoretically capable of performing up to 94% of tasks performed by computer and mathematics workers.
    4. Real Adoption Gap: Notes that despite this capability, Claude currently performs only about 33% of such tasks, indicating that technological potential exceeds current adoption.
    5. Declining Hiring Trends: Observes a 14% decline in hiring for younger professionals (22-25 years) in highly exposed occupations.
    6. Gender Dimension: Highlights that women constitute 54.4% of high-exposure roles compared to 38.8% of low-exposure roles, indicating potential gendered labour market impacts.
    7. Indian Context: A NITI Aayog report titled “Roadmap for Job Creation in the AI Economy” warns that over 60% of formal-sector jobs, particularly in IT services and BPO sectors employing over 6 million people, could face automation risks by 2030.

    How does the report measure AI exposure in the labour market?

    1. Observed Exposure Metric: Measures the extent to which AI is actually used in real work tasks by analysing usage patterns of Anthropic’s Claude AI model.
    2. Combination Approach: Integrates theoretical capability of LLMs with empirical usage data, creating a realistic understanding of labour market disruption.
    3. Correlation with Job Trends: Tests exposure levels against US government employment projections and unemployment survey data to identify links between AI exposure and labour market trends.
    4. Evidence-Based Findings: Establishes that higher AI exposure correlates with weaker job growth and rising job losses in certain occupations.

    Which sectors face the highest AI disruption risks?

    1. Business and Finance: AI systems can perform financial analysis, data interpretation, and report generation, increasing automation potential in financial services.
    2. Management Occupations: AI supports strategic planning, data analytics, and decision-support tools, reducing reliance on routine managerial tasks.
    3. Computer and Mathematical Jobs: LLMs show the highest capability in coding, debugging, and software documentation tasks, with theoretical capability covering 94% of such tasks.
    4. Legal Sector: AI assists in contract analysis, legal research, and document drafting, increasing exposure in legal professions.
    5. Office and Administrative Work: Routine administrative functions such as documentation, scheduling, and record management are highly susceptible to automation.

    Why are digital and knowledge-sector jobs more vulnerable than manual jobs?

    1. Digitisation of Work: Tasks performed in digital environments are easier for AI systems to replicate using algorithms and machine learning models.
    2. Routine Cognitive Tasks: AI excels in pattern recognition, data processing, and repetitive analytical tasks.
    3. Physical Constraints: Manual occupations involving physical movement, craftsmanship, or real-world interaction remain difficult for AI systems to automate.
    4. Lower AI Applicability in Manual Sectors: Industries such as construction, agriculture, protective services, and personal care show relatively lower AI exposure.

    How could AI affect employment patterns and demographics?

    1. Impact on Young Workers: Hiring in highly exposed occupations for workers aged 22-25 years has declined by 14%, suggesting reduced entry-level opportunities.
    2. Gender Disparity: Women represent 54.4% of high-exposure jobs, indicating disproportionate vulnerability in AI-driven labour market changes.
    3. Highly Educated Workforce Exposure: AI disruption is concentrated in graduate-level occupations, highlighting risks for knowledge workers rather than low-skilled labour.
    4. Occupational Polarisation: AI may lead to growth in high-skill innovation roles and low-skill manual jobs, while shrinking middle-skill occupations.

    What implications does AI disruption have for India?

    1. IT and BPO Sector Risks: Over 60% of formal-sector jobs in IT services and BPO industries may face automation pressures by 2030.
    2. Employment Scale: These sectors currently employ over 6 million people in India, making AI disruption economically significant.
    3. Stock Market Response: Shares of TCS, Wipro, and Infosys declined nearly 20% over the past year, reflecting investor concerns about AI-driven automation.
    4. Skill Gap Challenge: Limited mathematical and scientific skill levels among large segments of the population could hinder adaptation to AI-driven economies.
    5. Low R&D Investment: India’s low spending on research and development compared to the US and China reduces its capacity to lead in AI innovation.

    Can AI also create opportunities in traditional sectors?

    1. Precision Agriculture: AI-enabled analysis of satellite imagery, weather forecasts, soil data, and crop patterns enables farmers to optimise sowing and harvesting decisions.
    2. Agricultural Risk Reduction: AI systems provide early warnings about pests and diseases, improving crop protection.
    3. Resource Optimisation: AI helps farmers determine fertiliser use, irrigation requirements, and input efficiency.
    4. Policy Initiatives: The Union Budget 2026–27 proposed the Bharat-VISTAAR system (Virtually Integrated System to Access Agricultural Resources) to integrate AgriStack platforms with ICAR research data.

    Conclusion

    Artificial Intelligence is reshaping the nature of work by transforming how tasks are performed rather than simply eliminating jobs. The Anthropic report highlights that occupations involving digital and cognitive tasks face the greatest exposure to AI-driven automation. For India, where millions depend on knowledge-sector employment, the challenge lies in strengthening skills, promoting AI innovation, and ensuring that technological progress complements rather than displaces human labour.

    PYQ Relevance

    [UPSC 2023] Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?

    Linkage: This question directly relates to the applications and societal implications of AI, similar to how the article discusses AI transforming labour markets and professional work.

  • How did the space sector fare in the budget?

    Why in the News

    The Union Budget shows stable funding for the space sector after post-pandemic adjustments, following a 182% increase in allocations over the last decade. This reflects a shift from rapid expansion to fiscal consolidation. For the current year, the Budget has maintained broadly similar allocations for space activities, ensuring continuity for ISRO’s core programmes rather than announcing a major increase. However, industry bodies such as SatCom Industry Association (SIA)-India and Indian Space Association (ISpa) note that this stability has come without structural reforms, particularly in GST rationalisation, downstream enablement, and private sector incentives. The article highlights a gap between India’s space liberalisation framework, led by IN-SPACe, and the limited fiscal and regulatory support provided in the Budget.

    Has budgetary support for the space sector stabilised?

    1. Stabilised Allocations: Reflect a post-pandemic correction after a 182% increase in space spending over the past decade, signalling fiscal consolidation rather than retrenchment.
    2. Institutional Continuity: Ensures operational stability for ISRO, whose budget had earlier faced compression during COVID-19 years.
    3. Limited Expansion Signal: Indicates absence of new large-scale mission announcements or funding surges, reinforcing a maintenance-oriented fiscal posture.

    Does the Budget address structural reforms in the space ecosystem?

    1. Reform Gap: Ignores long-standing demands raised by SIA-India for taxation and policy rationalisation to support private and downstream firms.
    2. Public-sector Bias: Continues to prioritise ISRO’s upstream capabilities while underplaying ecosystem-wide enablement.
    3. Missed Alignment: Fails to integrate fiscal measures with the institutional role of IN-SPACe, which was created precisely to facilitate private participation.

    How does GST affect space industry competitiveness?

    1. GST Burden: High GST incidence on specialised inputs and imported components raises production costs for satellite and launch manufacturers.
    2. Cash-flow Stress: Refund delays under GST disproportionately affect private firms and startups operating under thin margins.
    3. Export Competitiveness: Weakens India’s cost advantage in global launch and satellite service markets, a concern explicitly flagged by industry bodies.

    What challenges exist for downstream space applications?

    1. Neglect of Applications: Budgetary focus remains skewed towards upstream launch and satellite programmes, with minimal fiscal support for applications.
    2. Commercial Bottlenecks: Affects communication, navigation, earth observation, and data analytics sectors that rely on satellite services.
    3. Innovation Constraints: Absence of PLI-type incentives for space manufacturing and services limits scale-up and market absorption.

    Is private participation adequately supported?

    1. Policy-Finance Disconnect: While liberalisation has been institutionalised through IN-SPACe, fiscal incentives remain absent.
    2. Investment Uncertainty: The Budget does not build upon the ₹1,000 crore venture capital fund announced in the previous Budget, offering no clarity on deployment or expansion.
    3. Ecosystem Imbalance: Growth remains anchored to state-led capabilities rather than a diversified commercial space economy.

    Conclusion

    The Budget secures stability for India’s space programme but does not translate liberalisation intent into fiscal or regulatory support. By overlooking GST reform, downstream incentives, and private investment facilitation, it risks slowing the transition from an ISRO-centric model to a competitive, market-driven space economy.

    PYQ Relevance

    [UPSC 2016] Discuss India’s achievements in the field of Space Science and Technology. How has the application of this technology helped India in its socio-economic development?

    Linkage: Space science and technology is a recurring GS-III theme, testing India’s indigenous technological capacity and its role in national development. The current Budget debate on space highlights the shift from mission achievements to ecosystem sustainability, making the socio-economic application and commercialisation of space technologies a critical evaluative dimension.

  • PFRDA forms high-level committee for assured payouts under NPS

    Why in the news?

    The Pension Fund Regulatory and Development Authority (PFRDA) has constituted a high-level committee to frame guidelines and regulations for assured pension payouts under the National Pension System (NPS), aimed at strengthening retirement income security.

    About the committee

    • Chairperson: Dr. M. S. Sahoo, Former Chairperson, Insolvency and Bankruptcy Board of India (IBBI)
    • Composition: 15 members from legal, actuarial, finance, insurance, capital markets and academia
    • Flexibility: Power to invite external experts and intermediaries as special invitees
    • Nature: Standing advisory committee on structured pension payouts

    Key objectives and terms of reference

    • Assured payout framework: Draft regulations for assured and structured pension payouts, based on PFRDA consultation paper dated 30 September 2025
    • Seamless transition: Smooth shift from accumulation phase to decumulation payout phase
    • Market based assurance: Explore novation and settlement mechanisms for legally enforceable guarantees
    • Operational design: Define lock in period, withdrawal limits, pricing mechanisms and fee structures
    • Risk and legal oversight: Specify capital and solvency norms and examine tax implications for in-system payouts
    • Consumer protection: Standardised disclosure framework to prevent mis selling and manage subscriber expectations

    Significance

    • Enhances predictability and security of retirement income
    • Strengthens trust and attractiveness of NPS
    • Supports the vision of Viksit Bharat 2047 with financial dignity in old age
    [2017] Who among the following can join the National Pension System (NPS)? 

    (a) Resident Indian citizens only 

    (b) Persons of age from 21 to 55 only 

    (c) All State Government employees joining the services after the date of notification by the respective State Governments 

    (d) All Central Governments Employees including those of Armed Forces joining the services on or after 1st April, 2004

  • If data is the new oil, what does that make data centres?

    Why in the News?

    India is increasingly seen as a likely destination for global “data dumping” as large data centres expand due to AI growth, government incentives, and geopolitical changes. This is a serious issue because data centres place heavy pressure on electricity, water, land, and environmental regulation, especially in water-stressed cities. Unlike earlier views that treated digital infrastructure as low-impact, data centres are now emerging as resource-intensive industrial units, raising concerns about sustainability, weak regulation, and long-term environmental costs.

    What are Data centers?

    1. Physical Digital Infrastructure: Large facilities that store, process, and manage digital data using servers, storage systems, and networking equipment.
    2. Backbone of the Digital Economy: Support cloud computing, e-governance, AI, fintech, e-commerce, and social media services.

    Why is India vulnerable to becoming a “data dumping” destination?

    1. Geopolitical Stability: Provides predictability compared to other global regions, increasing investor preference.
    2. Fiscal Incentives: Offers subsidised land, power, and expedited clearances for data infrastructure.
    3. Domestic Market Scale: Ensures long-term demand for data storage and processing.
    4. AI-Driven Demand: Accelerates need for hyperscale facilities with high energy density.

    Why are data centres no longer “clean” digital infrastructure?

    1. Electricity Intensity: Requires massive grid capacity, substations, and uninterrupted power supply.
    2. Water Dependence: Uses large volumes for cooling, especially where air cooling is not feasible.
    3. Thermal Pollution: Releases waste heat, intensifying urban heat stress.
    4. Industrial Footprint: Mirrors heavy industry in land use, emissions, and infrastructure strain.

    What environmental risks?

    1. Water Stress: Many Indian cities already face chronic water shortages.
    2. Grid Overload: Clustered data centres require grid upgrades and load balancing.
    3. Externalised Costs: Environmental and infrastructure costs often borne by the public sector.
    4. Weak Enforcement: Post-clearance monitoring and compliance remain inadequate.

    What are the governance and regulatory gaps?

    1. Institutional Lacunae: Noted by the Comptroller and Auditor General, Supreme Court, and National Green Tribunal.
    2. Zoning Weaknesses: Data centres not uniformly classified as heavy infrastructure.
    3. Opacity: Non-disclosure agreements restrict public scrutiny.
    4. Fragmented Oversight: Multiple agencies without integrated regulation.

    What lessons emerge from international and domestic resistance?

    1. United States Experience: Community resistance in Virginia, North Carolina, and Minnesota due to water and energy stress.
    2. Transparency Failures: Projects stalled due to non-disclosure and lack of public consultation.
    3. Course Correction: Developers increasingly engaging communities early to reduce backlash.
    4. Indian Parallel: Similar conditions exist but with weaker civic engagement and regulatory checks.

    Risks of unchecked expansion

    1. Capital Intensity: Limits government bargaining power once investments are sunk.
    2. Subsidy Distortions: Shifts public resources toward private digital infrastructure.
    3. Environmental Injustice: Local communities bear costs without proportional benefits.
    4. Governance Risk: Early-stage policy failures become irreversible later.

    Conclusion

    Data centres must be treated as heavy infrastructure, not neutral digital assets. Without enforceable zoning, water-use ceilings, transparent disclosures, and robust environmental oversight, India risks replicating extractive development models under the guise of digital growth. Sustainable digitalisation requires aligning data infrastructure with ecological limits and democratic accountability.

    PYQ Relevance

    [UPSC 2015] Discuss the advantages and security implications of cloud hosting of servers vis-a-vis in-house machine-based hosting for government businesses.

    Linkage: This question examines the trade-offs between efficiency-driven digital governance and strategic data control. It also connects with current debates on data centres, cloud infrastructure, and data sovereignty, where reliance on cloud hosting raises concerns of security, resilience, and regulatory oversight for government systems.

  • ‘Your Money, Your Right’ Movement  

    Why in the News?

    The Prime Minister recently urged citizens to actively participate in the ‘Your Money, Your Right’ movement, a national initiative to help people reclaim their unclaimed financial assets.

    About the Movement

    • Launched by the Central Government in October 2025.
    • Objective: Enable citizens to locate and recover unclaimed deposits, insurance proceeds, dividends, mutual fund amounts, and other financial assets.

    Scale of Unclaimed Funds in India

    • Banking sector: Rs 78,000 crore unclaimed.
    • Insurance companies: Rs 14,000 crore unclaimed.
    • Mutual funds: Rs 3,000 crore unclaimed.
    • Dividends: Rs 9,000 crore unclaimed.
    • Deposits lying idle for 10 years or more are classified as unclaimed deposits.

    Dedicated Portals for Easy Access

    • Unclaimed bank deposits
       • Regulatory Body: Reserve Bank of India
       • Portal: UDGAM Portal
    • Unclaimed insurance proceeds
       • Regulatory Body: Insurance Regulatory and Development Authority of India
       • Portal: Bima Bharosa Portal
    • Unclaimed mutual fund amounts
       • Regulatory Body: Securities and Exchange Board of India
       • Portal: MITRA Portal
    • Unpaid dividends and unclaimed shares
       • Regulatory Body: Ministry of Corporate Affairs
       • Portal: IEPFA Portal
    Pradhan Mantri Jan-Dhan Yojana’ has been launched for (2015)

    (a) providing housing loan to poor people at cheaper interest rates 

    (b) promoting women’s Self-Help Groups in backward areas 

    (c) promoting financial inclusion in the country 

    (d) providing financial help to the marginalized communities

  • [28th November 2025] Hindu OpED Are the labour codes labour friendly

    PYQ Relevance

    [UPSC 2024] Discuss the merits and demerits of the four ‘Labour Codes’ in the context of labour market reforms in India. What has been the progress so far in this regard?

    Linkage: The article’s debate on worker protection vs. industry flexibility directly reflects the merits and demerits raised in this PYQ. It also covers the slow implementation and stakeholder resistance, matching the question’s focus on progress.

    Mentor’s Comment

    The introduction of India’s four consolidated labour codes has triggered a high-stakes national debate on whether they truly modernise labour regulation or dilute long-standing protections. This article dissects the core arguments expanding them into a UPSC-focused analytical framework. The aim is to help aspirants understand the political economy of labour reforms, their implications for workers and industry, and their place in India’s growth policy discourse.

    WHY IN THE NEWS?

    India’s four consolidated labour codes, wage, social security, industrial relations, and occupational safety, have reignited debate as trade unions accuse the government of diluting protections while industries argue they streamline a fragmented regulatory environment. The issue is significant because India has not attempted such a comprehensive codification since Independence, and the codes come at a time when informal workers form 93% of the workforce but only 7% receive social security. The codes also affect hiring, firing, job security, and collective bargaining, core issues shaping labour productivity and industrial peace.

    INTRODUCTION

    India’s labour market operates at the intersection of rapid economic modernization and persistent structural informality. The four new labour codes aim to consolidate 29 existing laws, reduce compliance rigidity, support ease of doing business, and expand social security. However, the reforms have triggered disagreements between trade unions, who fear erosion of worker rights, and industries, who seek flexibility to improve competitiveness. This article examines the institutional debates and policy implications emerging from the new codes.

    The Historical Context of Labour Law Reform

    1. Fragmented Legislation: Consolidated 29 separate laws, many framed in the 1940s-50s, marked by overlapping definitions, multiple inspections, and differing interpretations across states.
    2. Changing Labour Landscape: Witnessed rapid industrial growth, gig work, platforms, logistics, contract labour, and digital-era employment, demanding updated regulatory structures.
    3. Productivity Imperatives: Industries argue workers must be protected and empowered but rigidities must reduce to strengthen India’s global competitiveness.

    What Necessitated the Labour Codes?

    1. Regulatory Overlap: Multiple laws with inconsistent provisions complicated compliance and enforcement.
    2. Economic Modernisation Need: Traditional industry structure gave way to gig work, platform work, logistics, e-commerce and new forms of employment, requiring modern regulation.
    3. Social Protection Gap: Only 7% of workers covered by social security; informal economy workers remain largely unprotected.
    4. Investment Climate Concerns: Procedural delays in hiring/firing, disputes, and closures deterred global investment.

    Do the Labour Codes Promote or Restrict Worker Rights?

    1. Trade Union Concern-Reduced Security: Fears that fixed-term contracts, easier retrenchment thresholds, and union restrictions weaken bargaining power.
    2. Collective Bargaining Apprehension: Codes allow only a single negotiating union, potentially marginalising smaller unions.
    3. Industry Perspective-Greater Formalisation: Codification ensures predictable rules, reduces litigation, and encourages job creation.
    4. Worker Protection Measures: Codes extend minimum wage applicability, mandate formalised contracts, introduce new safety norms, and expand the definition of employees.

    How Will the Codes Impact Social Security and Gig Workers?

    1. Social Security Expansion: Gig and platform workers added under social security, but benefits remain contingent upon schemes and government implementation.
    2. Funding Challenges: Industry argues government and employees must co-contribute; trade unions insist government should shoulder primary responsibility.
    3. Small Share of Gig Workers: Currently form a small slice of the informal sector but rapidly growing; require future-ready welfare structures.

    Do the Codes Improve Industrial Relations and Productivity?

    1. Industry View: Ensures Stability
      • Predictability and ease of compliance strengthen investment climate and reduce industrial disputes.
    2. Trade Union View: Risk of Industrial Unrest
      • Dissatisfaction due to inadequate representation and perceived dilution of rights may trigger strikes.
    3. Flexibility vs. Protection Debate: Government seeks a balance between global competitiveness and worker protection.

    Will the Codes Expand Organised Employment?

    1. Industry Assertion: Broader wage definitions, coverage of establishments, and social security norms bring more workers under formal sector protections.
    2. Union Counterpoint: Without job stability, contract labour proliferation may worsen precarity.

    CONCLUSION

    India’s labour codes represent an ambitious attempt to modernise outdated labour laws, enhance productivity, and integrate India into global manufacturing networks. However, the success of these reforms will depend on transparent implementation, a balanced approach to worker protection, and sustained dialogue with trade unions. A labour ecosystem that provides both flexibility and security is essential for equitable and sustainable growth.

  • [15th November 2025] The Hindu Op-ED: Flexible inflation targeting, a good balance

    Mentor’s Comment

    The debate on India’s Flexible Inflation Targeting (FIT) framework is central to macroeconomic stability, especially as the Reserve Bank of India (RBI) undertakes the second quinquennial review after adopting FIT in 2016. This article decodes the logic, data trends, inflation-growth dynamics, concerns over inflation bands, and the evolving economic context, translated into UPSC-ready analysis with conceptual clarity.

    Introduction

    India adopted the Flexible Inflation Targeting (FIT) framework in 2016, giving statutory autonomy to the RBI for price stability. With the current inflation band of 4% ± 2% up for review in March 2026, economic debate has intensified on whether this band remains appropriate amid structural shifts, supply-side shocks, and the inflation-growth trade-off. The article evaluates India’s experience with FIT, evidence from inflation-growth relationships, and the question of acceptable inflation levels for sustained macroeconomic stability.

    Why in the News?

    The FIT framework is undergoing its second major review since its inception in 2016, making it a crucial moment for India’s monetary policy architecture. RBI has released a research discussion paper, its most comprehensive assessment yet, presenting long-term inflation-growth data, the first such empirical mapping since 1991. The debate is significant because India’s inflation has remained near the upper tolerance band, raising questions about whether 4% is still an appropriate central target or whether persistent supply shocks require rethinking the framework. The outcome of this review will shape India’s monetary autonomy, fiscal-monetary coordination, and growth stability over the coming decade.

    What makes inflation control central to monetary policy?

    1. Inflation as a regressive tax: Disproportionately burdens poorer households whose incomes are not hedged; erodes purchasing power.
    2. High inflation leading to misallocation of resources: Leads to volatile investments and misdirected economic decisions.
    3. Acceptable inflation evolves with context: The Chakravarty Committee (1985) recommended 5% as acceptable, but economic conditions have since changed.
    4. Institutional strengthening since 1994: Post-automatic monetisation era gave RBI functional autonomy; FIT (2016) gave statutory backing for price stability.

    How does India’s current FIT framework work?

    1. Inflation band of 4% ± 2%: Offers flexibility while anchoring expectations.
    2. Headline inflation as target: Encourages investment protection from supply shocks; aligns with international norms.
    3. Range-bound inflation despite shocks: India has broadly maintained inflation within the band, reflecting maturing policy credibility.
    4. Mechanism evolves with economic complexity: Framework still young, but institutional autonomy makes it robust.

    What should India target-headline inflation or core inflation?

    1. Headline inflation captures supply shocks: Essential in an economy where food inflation significantly affects households.
    2. Misconception on price behaviour: General price level (inflation) differs from relative price changes (e.g., wages, food).
    3. Milton Friedman example: Excess money supply raises general prices; changing relative prices without liquidity expansion cannot cause inflation.
    4. No liquidity expansion leading to no general inflation: Relative price movement alone insufficient to generate sustained inflation.

    What does long-term data reveal about inflation and growth?

    1. Quadratic inflation-growth curve (1991-2023): Presented in the article; first time excluding COVID years.
    2. Point of inflection = 3.98%: Growth rises with inflation to ~4%, then declines beyond it.
      1. Implication: India’s acceptable inflation level is just around 4%.
    3. Higher inflation hurts growth: Especially when supply constraints, fiscal stress, and external pressures coincide.

    How flexible should the inflation band be

    1. FIT performance so far: Delivered flexibility; monetary authorities operate near upper limit due to shocks.
    2. Risk of staying at the upper band: May undermine framework credibility.
    3. Policy navigation matters: India earlier faced high inflation in the 1970s-80s; monetisation of the deficit made it worse.
    4. Present framework avoids past mistakes: Moves away from fiscal dominance; prevents automatic deficit monetisation.

    What determines an acceptable level of inflation?

    1. Phillips Curve insights: Countries with higher income also see higher acceptable inflation levels.
    2. Empirical threshold near 4%: RBI paper’s curve suggests growth maximisation at around 4%.
    3. India-specific vulnerabilities: Supply shocks (food, fuel), climate variability, imported inflation, fiscal constraints.
    4. Need for robust expectations anchoring: Prevents wage-price spiral and demand misalignment.

    Conclusion

    India’s Flexible Inflation Targeting has broadly succeeded in stabilising inflation expectations while preserving monetary autonomy. Evidence from long-term inflation-growth dynamics reinforces that 4% remains an optimal central target, though India must build greater resilience to supply shocks and strengthen fiscal-monetary coordination. A credible, flexible, and data-driven FIT framework remains essential for India’s growth trajectory over the next decade.

    PYQ Relevance

    [UPSC 2024] What are the causes of persistent high food inflation in India? Comment on the effectiveness of the monetary policy of the RBI to control this type of inflation.

    Linkage: This PYQ  is highly relevant as food inflation heavily shapes headline inflation under the Flexible Inflation Targeting (FIT) framework, highlighting the limits of the Reserve Bank of India’s (RBI) tools. It links to the review of the four-percent target and RBI’s role in managing supply-driven inflation.

  • [7th November 2025] The Hindu Oped: Redraw welfare architecture, place a UBI in the centre

    PYQ Relevance

    [UPSC 2015] In what way could replacement of price subsidy with Direct Benefit Transfer (DBT) change the scenario of subsidies in India? Discuss.

    Linkage: The shift from price subsidies to Direct Benefit Transfers (DBT) improved efficiency and targeting in welfare delivery. Universal Basic Income (UBI) is the next step in this evolution, moving from targeted transfers to universal, unconditional income support that ensures inclusion and economic stability.

    Mentor’s Comment

    As automation, artificial intelligence, and widening inequality reshape global economies, India faces an urgent need to rethink its welfare model. Universal Basic Income (UBI) , once dismissed as utopian, is emerging as a viable economic tool to balance growth with inclusion, stabilize consumption, and future-proof citizens against technology-driven disruptions.

    Introduction and Why in the News

    India’s wealth gap is at a 75-year high, and technological transformation is outpacing job creation. The article argues that a Universal Basic Income could act as a stabilizer for an economy characterized by automation-led job loss, consumption inequality, and welfare fragmentation. UBI thus represents both an economic necessity and moral evolution, a reform that can ensure social security while sustaining demand in an AI-driven economy.

    Understanding UBI in the Economic Context

    1. Concept: A periodic, unconditional cash transfer to all citizens, regardless of income or employment.
    2. Economic Foundation: Acts as a floor for consumption and stabilizer of demand during economic downturns.
    3. Rationale in India: Addresses inefficiencies, leakages, and exclusions in existing welfare subsidies and improves fiscal targeting through direct transfers.
    4. Global Relevance: Countries like Finland, Kenya, and Iran have experimented with variants of basic income to address automation shocks and inequality.

    Why India Needs a New Welfare Model

    • Automation and Jobless Growth:
      1. India’s labour-intensive sectors are losing relevance as AI and robotics replace routine work.
      2. A 2023 McKinsey Report estimates 40-45% of Indian jobs risk automation by 2030.
      3. Consumption Inequality: The top 10% hold over 40% of total income, weakening demand from lower strata, a key factor behind India’s K-shaped recovery post-COVID.
    • Fragmented Welfare Spending:
      1. Over 950 central schemes exist; only 20% reach intended beneficiaries (NITI Aayog, 2022).
      2. Rationalizing and merging subsidies could free 1-2% of GDP, enough to fund a phased UBI.

    Fiscal Feasibility and Implementation Models

    1. Budgetary Realignment: A UBI costing ₹7,500 per person annually = ~1% of GDP, fiscally manageable by pruning inefficient subsidies.
    2. Digital Readiness: India’s JAM Trinity (Jan Dhan-Aadhaar-Mobile) enables transparent Direct Benefit Transfers (DBT) to 450+ million beneficiaries.
    3. Phased Approach:
      • Start with vulnerable groups (elderly, women, informal workers) and expand gradually.
      • Link with automation tax or digital economy levy to ensure sustainability.
    4. Behavioral Economics View: Unconditional transfers improve human capital investment (nutrition, education) without creating disincentive to work, proven in Madhya Pradesh SEWA UBI Pilot, 2013.

    UBI as an Economic Stabilizer

    1. Counter-Cyclical Tool: Maintains aggregate demand in economic slowdowns; ensures liquidity among lower-income households.
    2. Productivity Boost: Financial security allows workers to upskill and pursue entrepreneurial ventures instead of insecure subsistence jobs.
    3. Gender Dividend: Recognizes unpaid care work and enhances female labour participation, a major economic multiplier.
    4. Rural Resilience: Ensures income continuity against climate shocks, agrarian distress, and market failures.

    Challenges in Adopting UBI

    1. Fiscal Trade-offs: High recurring costs could strain the fiscal deficit if not balanced by rationalization of subsidies.
    2. Inflationary Pressure: Sudden increase in liquidity may spike prices unless accompanied by supply-side reforms.
    3. Exclusion Risks via Aadhaar/DBT: Digital divide and authentication errors can replicate old exclusion patterns.
    4. Political Economy Resistance: Targeted benefits create patronage networks; universalization dilutes control, making reform politically sensitive.

    Global Insights for India

    Country Nature of UBI Trial Lessons
    Finland (2017-18) €560/month for unemployed Improved well-being, not joblessness
    Kenya Cash transfer for 12 years Increased small business formation
    Iran (2010) Universal transfer replacing subsidies Reduced poverty without fiscal collapse
    Brazil (Bolsa Família) Conditional transfer, near-universal Boosted literacy, health, consumption

    India can blend these experiences into a hybrid model: quasi-universal, fiscally prudent, and tech-enabled.

    Conclusion

    A Universal Basic Income is no longer a moral luxury, it is an economic inevitability in a future where automation, inequality, and climate shocks converge. By realigning subsidies and leveraging digital infrastructure, India can embed economic dignity into fiscal policy. UBI is not about welfare dependency, it is about stabilizing markets through empowered citizens.