Job Retention Support in Belgium During the Pandemic

 The evolution of job retention support in Belgium during the COVID-19 pandemic was characterized by a rapid scale-up of a pre-existing system, followed by a period of prolonged emergency measures and a gradual return to a modified version of its original framework.

Pre-Pandemic Foundation

Before the pandemic, Belgium already possessed a well-established but fragmented "temporary unemployment" system. This system comprised several sub-schemes to address different circumstances, such as economic difficulties (primarily for blue-collar workers), force majeure events (unpredictable outside events), and bad weather (crucial for the construction sector).

Crisis Evolution: The "Simplified" Scheme

In March 2020, the government responded to the pandemic by rapidly evolving the existing framework into a "simplified" force majeure coronavirus scheme. Key evolutionary changes included:

• Administrative Streamlining: Administrative procedures were simplified, notification periods were shortened from seven to three days, and the requirement for workers to submit monthly "control cards" was removed.
• Expanded Eligibility: Firm-level eligibility was granted to any company affected by lockdown measures, and worker-level requirements were loosened so that employees did not need to meet the usual minimum contribution history for unemployment benefits.
• Increased Generosity: The income replacement rate for workers was raised from 65% to 70% of gross earnings, supplemented by a daily payment from the National Employment Office (ONEM/RVA).
• Harmonization: The scheme removed many of the historical distinctions between blue- and white-collar workers, applying the simplified rules similarly to both groups.

Persistence and Delayed Phase-Out

A defining feature of Belgium's policy evolution was the long duration of these emergency measures. While many other OECD countries began reducing the generosity of their schemes as the first waves of the pandemic subsided, Belgium maintained its simplified framework with only minor adjustments.

• September 2020 Attempt: A brief attempt was made to restrict the simplified scheme to "severely impacted" sectors, but this was reversed by October 2020 as virus cases resurfaced.
• Extension to 2022: The simplified crisis scheme remained active until June 2022, significantly longer than similar programs in most other OECD countries.

Post-Pandemic Transitions and Future Directions

Following the expiration of the simplified scheme in mid-2022, Belgium began a phased return to its pre-pandemic framework, though some "transitional measures" remained in place until July 2023.

Recent and Proposed Evolutions:

• 2024 Adjustments: As of January 1, 2024, the replacement rate for temporary unemployment (except for force majeure) was lowered to 60%, and new daily employer supplements were introduced (EUR 5 for white-collar and EUR 2 for blue-collar workers).
• Structural Recommendations: The sources suggest the system should further evolve to include experience-rated employer contributions to discourage structural dependence and mandatory training incentives, as the Belgian scheme notably lacked the training components found in other countries like Germany or France.
• Simplification: Experts recommend fully eliminating the fragmented distinction between blue- and white-collar workers for economic temporary unemployment to modernize the system.

Take-up patterns of job retention support in Belgium during the COVID-19 pandemic were characterized by an unprecedented scale of participation, shifting worker demographics, and a strong correlation with firm productivity and prior experience.

Aggregate and Sectoral Trends

Belgium reached an unprecedented peak in April 2020, with nearly 30% of salaried employment (roughly one in three jobs) supported by the temporary unemployment scheme. This was significantly higher than the OECD average of just under 20%.

Usage was heavily concentrated in specific sectors:

• Historically High-Usage Sectors: Before the pandemic, support was primarily used for seasonal or cyclical reasons in construction, manufacturing, and administrative services.
• Pandemic-Impacted Sectors: During the crisis, take-up surged in sectors exposed to containment measures, most notably accommodation and food services, which saw massive spikes despite minimal pre-pandemic reliance on the scheme.
• Low-Usage Sectors: Sectors such as public administration, education, and finance saw minimal take-up.

Firm-Level Selection

Participation varied significantly based on firm characteristics, specifically productivity and history:

• Productivity: Less productive firms were much more likely to use the scheme. During the pandemic, 16.6% of workers in the least productive firms were placed on support, compared to only 6.4% in the most productive firms. This suggests that liquidity and financial constraints were major drivers of adoption. (Notably, the accommodation and food sector was an exception where more productive firms were more likely to use support, likely due to a desire to retain highly skilled staff in larger establishments).
• Prior Experience: Previous familiarity with the system was a strong predictor of pandemic use. 51% of firms with a history of using temporary unemployment (from 2017–2019) utilized the scheme during the crisis, while only 14% of new users did so.

Worker Demographics

The pandemic triggered a major shift in the types of workers receiving support:

• Shift to White-Collar Workers: Pre-pandemic, blue-collar workers accounted for over 90% of recipients. At the crisis peak in Q2 2020, however, white-collar workers comprised 43% of all recipients. While this share declined as the pandemic subsided, it remained higher than historical levels, suggesting some firms became more accustomed to placing white-collar staff on the scheme.
• Educational Attainment: Take-up was starkly divided by education. In 2020, 20% of low-educated workers received support compared to just 3% of highly educated workers.
• Other Characteristics: Support was also more prevalent among men (reflecting their concentration in construction and manufacturing) and workers with foreign nationalities.

Drivers of Take-up and Persistence

The primary driver of take-up across OECD countries was the stringency of containment measures (lockdowns). However, design features also played a role. In Belgium, the absence of direct employer co-financing for hours not worked likely contributed to both the high volume of claims and the persistence of usage.

While most OECD countries saw take-up drop to negligible levels (less than 1%) by late 2022, Belgium’s take-up remained elevated at around 2–3%. This persistence is attributed to a "structural dependence" where some firms use the scheme as a regular flexibility tool rather than an emergency response.

The impact assessment of Belgium’s job retention support during the COVID-19 pandemic reveals a system that was highly effective at its peak in preserving employment but also one that eventually dampened labor market dynamism and productivity-enhancing reallocation due to its prolonged duration.

1. Effectiveness in Job Preservation

The primary success of the Belgian scheme was its ability to avert massive unemployment during the acute phase of the crisis.

• Scale of Impact: At the peak of the pandemic (Q2 2020), the scheme is estimated to have averted an employment loss of 12.9% in Belgium. This was significantly higher than the cross-country average of 8%.
• Efficiency Ratio: For every 100 workers placed on the scheme in Belgium, 55 jobs were preserved.
• Targeting by Occupation: The impact was most pronounced in non-teleworkable occupations, which were most vulnerable to lockdowns. In contrast, the scheme had negligible effects on teleworkable occupations, which were less exposed to containment measures.

2. Impact on Productivity and Reallocation

While successful in the short term, the sources highlight significant concerns regarding the scheme's impact on the "normal functioning" of the labor market as the crisis subsided.

• Disruption of the "Job Ladder": Before the pandemic, Belgium’s labor market grew by reallocating workers from low-productivity firms to high-productivity firms through voluntary "job-to-job" mobility. The job retention scheme disrupted this by reducing separations in less productive firms.
• Dampened Growth: Because less productive firms were the primary users—covering 16.6% of their workers compared to 6.4% in the most productive firms—the scheme effectively kept workers "stuck" in less productive roles.
• Persistence Issues: This suppression of productivity-enhancing reallocation lasted well into 2022, even as job vacancies reached record highs. The sources suggest this likely hampered aggregate productivity growth during the recovery phase.

3. Deadweight Effects and Cost

The "deadweight effect"—defined as support given to jobs that would have been retained anyway or were not viable regardless of support—is estimated at 45% for Belgium. This is considered moderate and is comparable to historical data from the Great Recession, though slightly higher than more recent estimates for similar schemes in Spain (25%).

4. Demographic and Firm-Level Impacts

The impact of the scheme was not uniform across the economy:

• Education Gap: The scheme supported 20% of low-educated workers in 2020, compared to only 3% of highly educated workers, highlighting its role in protecting more vulnerable labor market segments.
• Firm Productivity: There was a clear negative correlation between firm productivity and take-up; the least productive firms used the scheme much more intensively, driven largely by liquidity constraints.
• Delayed Phase-Out: Because Belgium was slower than other OECD countries to scale back generosity, the continued high take-up eventually had small negative effects on employment as pandemic restrictions were lifted, as it hindered necessary labor market adjustments.

Based on the sources, the key recommendations for refining Belgium's "temporary unemployment" system focus on balancing immediate crisis protection with the need to maintain a dynamic and productive labor market. The sources identify four main pillars for future policy evolution:

1. Modulating Costs to Discourage Structural Dependence

A primary recommendation is the introduction of experience-rated employer contributions to reduce what the sources describe as "structural dependence" on the system.

• Addressing High Baseline Take-up: While most OECD countries saw take-up drop below 1% post-pandemic, Belgium’s usage remained at 2–3%, suggesting some firms use the scheme as a regular flexibility tool rather than for emergency response.
• Linking Usage to Contributions: By linking the use of the scheme to increases in future social security contributions, firms that frequently rely on temporary unemployment for seasonal or predictable fluctuations would contribute more to its financing.
• Targeted Incentives: Following models used in France or the United States, this system would discourage the use of public funds for predictable business patterns without re-enforcing liquidity constraints for firms facing genuine, unexpected shocks.

2. Timely Removal of Crisis-Related Generosity

The sources recommend more strictly aligning the generosity of the scheme with the severity of the crisis to avoid disrupting normal labor market functions.

• Phasing Out Emergency Measures: Belgium maintained its "simplified" crisis scheme significantly longer than other countries, which may have contributed to persistent take-up and slowed the reallocation of workers to more productive firms.
• Re-introducing Requirements: Policymakers are encouraged to re-introduce firm eligibility requirements (such as proof of declining turnover) or sector-specific restrictions earlier in the recovery phase to ensure support is targeted only to viable jobs at risk.

3. Simplifying and Unifying the System

To modernize the framework, the sources suggest simplifying the fragmented nature of the different sub-schemes.

• Eliminating Worker Distinctions: A major proposal is to fully eliminate the historical distinction between blue- and white-collar workers for economic temporary unemployment.
• Administrative Efficiency: Unifying these rules would reduce administrative complexity for employers and align the system with broader Belgian efforts to harmonize labor market statuses.

4. Embedding Training and Upskilling

The sources highlight that periods of reduced working hours represent a "missed opportunity" for investing in human capital, particularly for low-educated workers who were over-represented among recipients.

• Incentivizing Training: Future reforms should create a clear framework where prolonged support could be made conditional on training participation, similar to programs in Germany, France, and Austria.
• Long-Term Employability: Integrating training incentives can signal the viability of jobs while ensuring the workforce acquires in-demand skills that provide added value once they return to full capacity.

Comparing Belgium's job retention support to other OECD countries during the COVID-19 pandemic reveals a system that was unusually high in participation and persistent in its duration, though it ranked lower in financial generosity for average earners due to its specific targeting.

1. Scale of Take-up and Participation

Belgium saw an unprecedented surge in the use of its "temporary unemployment" scheme, significantly exceeding international averages.

• Unprecedented Peak: At the height of the crisis in April 2020, Belgium supported nearly 30% of its salaried employment, which was notably higher than the OECD average of just under 20%.
• Structural Persistence: While most OECD countries saw take-up drop to negligible levels (less than 1%) by late 2022, Belgium's participation remained elevated at 2–3%. This suggests a "structural dependence" where some Belgian firms continue using the scheme as a regular flexibility tool rather than for emergency shocks.

2. Generosity and the Synthetic Indicator

To compare across nations, the sources use a synthetic indicator measuring eligibility, work-sharing, and government generosity.

• Lower Initial Ranking: At the pandemic’s peak, Belgium’s "effective generosity" ranked in the lower third of OECD countries. This was primarily because Belgium's benefit cap resulted in a replacement rate of only 45% for average-wage workers, compared to the 71% OECD average.
• Targeting Low-Wage Workers: Conversely, the scheme was well-targeted for more vulnerable groups; for low-wage earners (67% of average wage), Belgium's replacement rate was 74%, closer to the 81% OECD average.
• Reversed Ranking by 2022: Because Belgium maintained its emergency measures while other countries scaled back, by the end of 2022, its scheme was among the most generous and widely used in the OECD.

3. Policy Evolution and Phase-Out Timing

A major point of divergence was the duration of emergency support.

• Delayed Normalization: Most OECD countries began reducing scheme generosity or phasing out temporary programs as the first waves subsided in 2021. In contrast, Belgium maintained its "simplified" crisis scheme until June 2022 and only fully returned to pre-pandemic rules in July 2023.
• Co-financing: Similar to many OECD peers at the start of the pandemic, Belgium removed direct employer co-financing for hours not worked. However, the absence of these requirements for a prolonged period likely contributed to the scheme's persistence compared to countries that re-introduced firm-level costs earlier.

4. Employment Effectiveness

Despite the high cost and persistence, the Belgian scheme was highly effective in its core mission.

• Jobs Saved: Belgium is estimated to have averted an employment loss of 12.9% at the pandemic's peak, significantly better than the 8% cross-country average.
• Efficiency and Deadweight: For every 100 workers on the scheme, Belgium preserved 55 jobs (compared to an average of 52 across other countries). The estimated deadweight effect (supporting jobs that would have been kept anyway) was 45%, which is considered moderate and slightly lower than the 48% average across the 22 European OECD countries studied.

5. Training: A Missed Opportunity

One area where Belgium lagged behind its neighbors was the integration of upskilling.

• Absence of Incentives: Unlike Germany, France, and Austria, which successfully integrated training incentives or requirements into their crisis schemes, Belgium’s temporary unemployment system did not include any direct training components.
• Barriers to Implementation: This was largely due to administrative fragmentation between national benefit payment bodies and regional training services.

Economic Survey 2025 26

 The following text is a reproduction of the key findings and sections from the Economic Survey 2025-26 as summarized in the sources:

Report Overview

The Economic Survey 2025-26 was tabled in Parliament by Finance Minister Ms. Nirmala Sitharaman on January 29, 2026.

State of the Economy

• GDP Growth: Real GDP growth for 2026-27 is projected to be between 6.8% and 7.2%. For 2025-26, the growth is estimated at 7.4%, a significant increase from 6.5% in the previous year. This growth is largely driven by domestic demand, with private final consumption expenditure reaching 61.5%, its highest level since 2011-12.
• Inflation: Retail inflation declined to 1.7% in 2025-26 (April-December), down from 4.6% in 2024-25. This decline, driven by lower food prices, has improved real purchasing power. However, the RBI and IMF project a gradual increase in inflation for 2026-27.
• External Sector: The current account deficit (CAD) was 0.8% of GDP in the first half of 2025-26. FDI inflows reached USD 81 billion in 2025, which is 13% higher than the previous year, though the Survey noted they remain below potential. As of mid-January 2026, forex reserves covered about 11 months of imports.

Government Finances

• Fiscal Deficit: The central government is estimated to keep the fiscal deficit below 4.5% of GDP for 2025-26.
• Debt Policy: The government has shifted to targeting the debt-to-GDP ratio until 2031 rather than following annual fiscal deficit targets, allowing for policy flexibility in an uncertain global environment. A return to a rule-based regime (targeting 3% deficit and 50% debt) may be considered after 2031.
• State Finances: The aggregate fiscal deficit of states rose to 3.2% of GDP in 2024-25, with only 11 states recording a revenue surplus.

Sectoral Highlights

• Agriculture: This sector recorded its highest decadal growth (4.5%) between 2015-16 and 2024-25. While livestock and fishing showed strong performance, crop yields remain constrained by structural gaps like fragmented landholdings.
• Industry: Growth reached 7% in the first half of 2025-26. The Survey highlighted that national R&D expenditure at 0.64% of GDP is insufficient and noted that the business sector's contribution to R&D (41%) is low compared to peers like China (77%).
• Services: Accounting for 54% of GDP, the sector grew by 9% in early 2025-26. Emerging opportunities were identified in data centres, niche tourism, and space and ocean services.

Employment and Workforce

• Labor Indicators: The unemployment rate fell to 3.2% in 2023-24, and female labor force participation increased to 42%.
• Gig Workers: Currently representing 2% of the workforce, gig workers are projected to reach 6.7% by 2029-30. The Survey emphasized the need for better social security and income support for these workers.

Emerging Challenges

• AI Adoption: The Survey recommended that India focus on application-led innovation and human capital rather than replicating frontier-scale models.
• Climate Change: Roadblocks include a lack of critical minerals and storage systems, with climate finance remaining a "binding constraint".
• Urbanisation: Institutional issues such as fragmented municipal governance and limited fiscal autonomy persist. The Survey suggests unlocking land through clearer titles and transit-oriented development.

OECD Supervision of Artificial Intelligence in Finance

 Financial supervision in the context of AI in finance is defined as the practical enforcement mechanism of financial regulation, acting as a dynamic process where rules and policies are interpreted to ensure compliance and assess emerging risks. While regulation provides the legal foundation, supervision focuses on identifying and managing risks to market integrity and stability.

Core Principles of Supervisory Approaches

Despite jurisdictional variations, supervisory approaches to AI are anchored in two foundational principles:

• Technology Neutrality: This principle dictates that existing regulatory requirements remain applicable regardless of the technology used to deliver a service. The sources note that advances in technology do not render safety, soundness, or compliance standards obsolete; rules generally apply whether a decision is made by AI, traditional models, or humans.
• Risk-Based Approach: Supervisory resources and interventions are prioritized based on the relative risk profile of a financial institution or sector. This allows for more intensive focus on entities or activities posing higher risks to stability or consumer protection.

Spectrum of Jurisdictional Approaches

Supervisory methods vary based on how they incorporate AI into their oversight:

• Leveraging Legacy Frameworks: Some regions, like the UK, primarily rely on established, principles-based frameworks to guide oversight.
• Developing AI-Specific Guidance: Others, such as Singapore, have developed dedicated AI governance principles (e.g., the FEAT framework) to guide the sector in addressing specific AI challenges.
• Integrating Cross-Sectoral Rules: In the EU, the AI Act incorporates AI-specific requirements for "high-risk" use cases in banking and insurance within a broader cross-sectoral regulation that must be integrated into existing supervisory strategies.

Challenges in Practical Implementation

The sources highlight several complexities that arise when translating technology-neutral policies into practice:

• Regulatory Interplay: Challenges emerge from the interplay between existing sectoral regulations and new AI-specific or cross-sectoral frameworks. Layering new AI rules on top of pre-existing rules can complicate supervisory mandates and increase compliance complexity for firms.
• Third-Party Dependency: There is a growing reliance on non-supervised entities, such as third-party technical vendors, which often operate outside the formal oversight of financial regulators. Supervisors are increasingly focusing on a firm’s capability to manage these dependencies through due diligence and contractual controls.
• Data and Monitoring Gaps: A lack of standardized definitions and comprehensive data on AI adoption complicates the assessment of usage and associated vulnerabilities.

Evolving Supervisory Practices

To balance innovation with stability, several practices are being adopted:

• Calibrated Guidance: In jurisdictions where firms report ambiguity, supervisors are considering carefully calibrated guidance on interpreting high-level principles to provide legal certainty.
• Public-Private Cooperation: Supervisors are engaging in novel initiatives like regulatory sandboxes and AI model testing (e.g., the UK FCA's AI Live Testing) to foster mutual understanding and support model validation in controlled environments.
• Investment in SupTech: Authorities are investing in upskilling and the deployment of AI-driven Supervisory Technology (SupTech) tools to enhance large-scale data analysis, market surveillance, and real-time monitoring.
• Pushing Tech Neutrality: The sources suggest that the unique speed and complexity of AI may eventually require supervisors to move beyond strict tech-neutrality by adopting technology-specific methodologies or metrics to assess acceptable levels of robustness, fairness, and explainability.

The supervision of AI in finance faces significant challenges primarily due to the intrinsic characteristics of AI innovation, such as the rapid pace of its evolution, the complexity and opaqueness of underlying technologies, and its increasingly autonomous nature. While regulation provides the legal foundation, supervisors must navigate the practical implementation of these rules in a dynamic environment where traditional oversight mechanisms may struggle to keep pace.

1. Technical and Operational Complexities

• The "Black Box" Problem: The inherent opacity of advanced AI models—often described as a "black box"—makes it difficult for supervisors to understand how results are generated. This limited explainability hinders the ability to deconstruct a model's rationale for specific outcomes, such as credit decisions, which is essential for ensuring accountability and regulatory compliance.
• Model Risk Management (MRM): While existing MRM frameworks are intended to be technology-neutral, the probabilistic nature and dynamic adaptability of AI models (which learn and change over time) create difficulties for traditional validation and performance monitoring protocols.
• Robustness and Reliability: Issues like "hallucinations" in generative AI and anthropomorphism (treating AI as human-like) pose risks to the robustness of model outputs, making it hard for firms to ensure consistent and reliable performance.

2. Data and Monitoring Gaps

• Lack of Granular Data: Financial authorities often lack comprehensive, standardized data on how AI is being adopted across the sector. This data gap is exacerbated by a lack of common taxonomies and definitions, which complicates the assessment of systemic vulnerabilities.
• Third-Party Dependency: There is a growing reliance on a small number of non-supervised third-party vendors for AI infrastructure and models. Because many of these providers operate outside the formal regulatory perimeter, supervisors face challenges in monitoring concentration risks and ensuring that financial firms maintain adequate control over outsourced functions.

3. Ethical and Governance Hurdles

• Fairness and Bias: The lack of transparency in AI models makes it difficult to detect and mitigate algorithmic bias, which can lead to discriminatory outcomes in areas like lending or insurance. Verifying the efficacy of a firm's bias-detection strategies is a complex task for supervisors due to the technical sophistication required.
• Human Oversight: Defining the practical application of "human in the loop" is reported as a challenge. Furthermore, "automation bias"—where humans place excessive trust in machine-generated results—can undermine the effectiveness of human oversight and decision-making.

4. Institutional and Regulatory Challenges

• Regulatory Interplay: In jurisdictions introducing new AI-specific rules (like the EU AI Act), layering these requirements on top of legacy frameworks can create ambiguity and increase compliance complexity. This interplay requires careful coordination to avoid overlaps or conflicting legal obligations.
• Supervisory Capacity and Skills: Effective oversight requires a multidisciplinary approach involving data scientists, engineers, and legal experts. Most authorities identify a significant need for upskilling and investment in technical expertise to monitor complex AI systems and deploy their own AI-driven supervisory tools (SupTech).

Supervisory practices in the financial sector are evolving to translate high-level regulations into effective oversight of AI innovation. While most jurisdictions rely on technology-neutral and risk-based approaches, they are increasingly adopting specific practices to balance the promotion of responsible AI with the need for market stability and consumer protection,,.

1. Calibrated Guidance and Interpretative Clarifications

Authorities are moving toward providing carefully calibrated additional guidance to address perceived ambiguities in existing principles-based frameworks,.

• Model Risk Management (MRM): Guidance is being issued to clarify how legacy MRM frameworks—originally designed for simpler models—apply to the technical specificities of AI, such as its dynamic adaptability and probabilistic nature,.
• Explainability and Fairness: Some supervisors have clarified operational expectations for explainability, such as France's four levels of explanation (observation, justification, approximation, and replication) based on the target audience and business risk.
• Sector-Specific Integration: In regions like the EU, supervisors are working to integrate new AI-specific rules (e.g., the AI Act) into existing sectoral frameworks to streamline compliance and avoid overlapping mandates,.

2. Public-Private Cooperation and Novel Testing

Direct engagement with the industry is seen as vital for deepening supervisors' understanding of practical AI deployment.

• Regulatory Sandboxes: These controlled environments allow firms to test AI models under direct supervision, helping to identify legal and operational challenges at an early stage.
• AI Live Testing: Novel initiatives, such as the UK FCA’s AI Live Testing, allow firms to trial models in real-world conditions while receiving regulatory guidance on output-driven validation and robustness metrics,.
• Collaborative Forums: Jurisdictions like Japan have launched public-private AI forums to discuss cross-cutting issues like data protection, talent development, and the prevention of financial crimes.

3. Investment in Capacity and SupTech

Effective oversight requires supervisors to have technical expertise that matches the complexity of the systems they monitor.

• Upskilling: A majority of OECD countries are actively engaged in training initiatives to combine domain-specific financial expertise with a deeper technical understanding of AI.
• SupTech (Supervisory Technology): Authorities are deploying AI-driven tools to enhance their own oversight functions, such as market surveillance, large-scale data analysis, and automated compliance verification.
• ECB Examples: The European Central Bank's SupTech Hub utilizes tools like "Athena" for analyzing supervisory documents and "Agora" for querying data lakes using natural language.

4. Inter-Agency and Cross-Border Coordination

Because AI is cross-cutting, financial supervisors are increasingly collaborating with other authorities and international peers,.

• National Level: Collaboration with digital or data authorities helps ensure policy alignment and reduces the complexity of multiple regulatory regimes.
• International Level: Cross-border information sharing is used to identify emerging vulnerabilities and prevent regulatory arbitrage in globally active financial markets,.

5. Adapting Methodologies and "Tech Neutrality"

There is an ongoing discussion about whether the speed and complexity of AI might require pushing the boundaries of technology neutrality.

• Technology-Specific Metrics: Supervisors may eventually need to adopt specific methodologies or quantitative metrics to assess acceptable levels of model robustness, fairness, and explainability,.
• Dynamic Oversight: Maintaining a flexible and adaptive stance allows oversight to keep pace with technological advances while ensuring the supervisory toolkit remains fit for purpose,.

In the context of supervising AI in finance, coordination efforts are considered vital because AI is inherently cross-cutting, often involving authorities and issues that extend beyond the traditional financial sector. These efforts aim to build a collective understanding of emerging risks, coordinate enforcement action for cross-border activities, and facilitate more coherent oversight frameworks.

National and Inter-Agency Coordination

At the domestic level, coordination is essential to manage the evolving supervisory architecture where multiple bodies may have overlapping remits.

• Simplification and Clarity: Coordination between financial authorities and other agencies (such as digital or data protection authorities) helps ensure policy alignment and reduces the complexity for firms trying to understand how multiple regimes apply.
• Institutional Examples: In Singapore, the Infocomm Media Development Authority (IMDA) works alongside the Monetary Authority of Singapore (MAS) on AI governance. In the EU, the implementation of the AI Act involves a complex web of national Market Surveillance Authorities, the AI Office, the AI Board, and European Supervisory Authorities (ESAs).
• Avoiding Overlap: Without effective inter-agency collaboration, regulated entities may face conflicting legal obligations or lower standards of conduct if new AI-specific guardrails do not reconcile with existing sectoral laws.

International and Cross-Border Collaboration

Because AI systems often traverse national barriers, international cooperation is necessary to maintain market integrity and prevent regulatory arbitrage.

• Identifying Vulnerabilities: Cross-border information sharing, such as efforts around incident reporting, helps supervisors identify emerging systemic vulnerabilities in globally interconnected markets.
• Consistency for Global Firms: Marked divergence in supervisory practices across jurisdictions can undermine the confidence of global market participants and discourage investment.
• Standardization: Coordination at the international level is needed to develop a common supervisory language, standardized definitions (e.g., for "General Purpose AI"), and common metrics for data collection.

Public-Private and Multidisciplinary Engagement

Supervisors are increasingly engaging with the private sector and academia to bridge the gap between high-level principles and technical implementation.

• Novel Testing Initiatives: Programs like the UK FCA’s AI Live Testing and Japan's Public-Private AI Forum cultivate dialogue between developers and regulators to support model validation and align supervisory expectations with industry realities.
• Multidisciplinary Approach: Effective oversight requires a mix of legal, economic, and technical expertise (such as computer engineers and data scientists); coordination allows for the strategic pooling of this institutional capacity.

Strategic Pooling for SupTech

Operational coordination is particularly important for the development of AI-driven Supervisory Technology (SupTech).

• Resource Constraints: Developing advanced SupTech requires significant financial investment and infrastructure. Collaborative efforts allow authorities to pool resources and share knowledge, reducing duplication of efforts.
• Joint Projects: Examples include the BIS Innovation Hub’s Project Aurora, which tests AI for anti-money laundering (AML), and the sharing of best practices for tools like the ECB’s textual analysis platform, "Athena".

Newspaper Summary 050226

 Anthropic’s launch of new automation plug-ins for its Claude Cowork agent has rattled global technology markets, triggering a sell-off in software stocks and intensifying investor concerns that advanced AI could disrupt labor-heavy outsourcing models. India’s IT services sector has emerged as one of the most exposed to this shift.

What did Anthropic announce?

Anthropic launched plug-ins for its Claude Cowork agent designed to automate specialized tasks across various organizational functions, including sales, productivity, marketing, legal, finance, customer support, and bio research.

• Legal: The plug-in speeds up contract reviews, NDA triage, and compliance workflows.
• Sales: It assists with prospecting, outreach, pipeline management, and deal strategy.
• Enterprise Search: This feature treats all of a company's tools—such as email, chat, and cloud storage—as a single searchable knowledge base.
• Customer Support: Claude acts as a support co-pilot, triaging tickets and researching queries across multiple sources to draft tailored responses.

How did markets react?

The Nifty IT index fell 6.6% on the day of the announcement, led by significant losses in major Indian tech stocks:

• Infosys: -7.99%
• Coforge: -7.6%
• TCS: -7.01%
• LTIM: -6.52%
• HCLTech: -4.85%
• Wipro: -4.51%

This sentiment extended to the U.S. markets, where Indian American Depository Receipts (ADRs) also declined; Infosys ADR fell 5.56% and Wipro ADR dropped 4.83%.

Why did the launch spook investors?

Experts noted that Anthropic’s tools stoked global fears that advanced AI could quickly replace a wide range of outsourced services. Investors are increasingly concerned that foundation models like Claude could bypass traditional SaaS platforms and IT service providers.

Why is India’s IT sector vulnerable?

Indian IT companies have traditionally relied on a labor-intensive, services-led model rather than being product-driven,. Because these firms have historically handled the manual and data-heavy tasks that AI is now capable of automating with far less human involvement, the industry faces:

• Rising competition from AI models.
• Weaker demand for conventional outsourcing.
• Margin pressure across software companies.

The prevailing market view is shifting: AI is no longer seen just as a tool that supports software firms, but as a potential replacement for them.

Impact on other sectors

The launch has also heightened fears within the legal ecosystem, negatively impacting stocks for legal software and publishing companies. While some AI startups are automating legal work, Anthropic stands out as a model builder that can customize AI for specific industry needs. This capability allows it to disrupt traditional legal data providers and the very startups that rely on its models, potentially eroding the core business of legal information services.

Any foreign company providing cloud services through a data center in India will be granted a tax exemption, provided they meet four specific conditions, according to Finance Ministry sources.

The Tax Holiday Proposal

In her Budget speech, Finance Minister Nirmala Sitharaman proposed a tax holiday lasting until 2047 for foreign companies that use Indian data center services to provide cloud services to global customers. The exemption is set to be available from the tax year 2026-27 through 2046-47.

Additionally, the Minister proposed a safe harbour margin of 15% on costs for cases where the Indian data center providing the services is a related entity (a cost-plus center) of the foreign company.

The Four Essential Conditions

To qualify for this tax exemption, a foreign company must satisfy the following requirements:

1. The foreign company must be notified.
2. The data center services in India must be procured from an Indian company.
3. The data center itself must be notified by the Ministry of Electronics and Information Technology (MeitY).
4. Any services provided by the foreign company to Indian users must be routed through an Indian reseller entity that is also an Indian company.

Objectives and Impact

• Tax Certainty: The move aims to provide certainty to global cloud providers, ensuring their global income is not taxed in India simply because they utilize Indian data centers.
• Level Playing Field: Officials state this creates a level playing field where Indian data centers can confidently pitch their services to global entities without the latter perceiving a tax risk.
• Global Parity: Industry experts, such as Piyush Somani of ESDS Software Solution, noted that this move offers parity with jurisdictions like Ireland and Singapore, which already do not heavily tax such entities.
• Domestic Taxation: Profits derived from domestic activities—such as the data center's services to the global entity and the reseller's services to Indian customers—will remain taxable as they would be for any other domestic firm.

Industry Perspectives

While the move is seen as a way to boost investment in critical infrastructure, some local players have raised concerns. Abhishek Bhatt of the Bharat Digital Infrastructure Association suggested that sectors vital to national security should be reserved exclusively for Indian cloud providers to prevent the country from becoming a "reseller economy".

Commerce Minister Piyush Goyal, in a statement to Parliament regarding the India-US trade deal, emphasized that ensuring the energy security of 1.4 billion Indians is the government's “supreme priority.”

Conflicting Stances on Russian Oil

While the White House insists that India has committed to halting the purchase of Russian oil as part of the trade agreement, Minister Goyal did not directly refute this claim. Instead, he maintained that India's strategy is centered on diversifying energy sourcing based on objective market conditions and evolving international dynamics. He stated that all of India’s actions are taken with this priority in mind.

Details of the Trade Deal

The deal involves significant tariff adjustments:

• US Tariffs on India: Reduced to 18% from 50%.
• Indian Tariffs on US Exports: Reduced to 0%.

White House Press Secretary Karoline Leavitt described the agreement as a “great deal and a huge win” for American workers, businesses, and consumers.

Fluid Negotiations

Sources indicates that the final terms regarding Washington’s position on India’s oil purchases remain fluid. It is not yet clear if the US will push the Russian oil issue during the technical negotiations. The deal is expected to be formally signed once the negotiating teams finish the paperwork and finalize a joint statement, which will reflect any final decisions on the oil purchase issue.

Additionally, Goyal noted that India successfully safeguarded its interests in sensitive sectors, specifically agriculture and dairy, within the agreement.

Trent Ltd reported a 41 per cent increase in standalone profit after tax to ₹660 crore for the third quarter ended December 31, 2025, driven by robust growth in its fashion retail business. Revenue from operations grew 16 per cent to ₹5,259 crore.

Financial Highlights

• Operating EBITDA: Rose 23 per cent to ₹822 crore in Q3 FY26.
• EBIT Margin: Expanded to 13.8 per cent from 13.2 per cent a year ago.
• Nine-Month Performance: Standalone PAT grew 24 per cent to ₹1,534 crore, while revenue increased 18 per cent to ₹14,765 crore.
• Consolidated Results: Reported revenue of ₹5,345 crore (up 15%) with PAT at ₹531 crore (7% growth), including the proportionate share from the Trent Hypermarket joint venture.

Aggressive Store Expansion

The company continued its rapid physical expansion during the quarter, adding 17 Westside and 48 Zudio stores, including a Zudio outlet in the UAE. As of December 31, 2025, Trent's total footprint includes:

• 278 Westside stores.
• 854 Zudio stores (including four in the UAE).
• 32 other lifestyle concept stores across 274 cities, spanning over 15 million square feet of retail space.

Leadership Perspective

Chairman Noel N Tata stated that the fashion business achieved category-leading growth despite a higher base. He noted that customer sentiment is gradually improving and the medium-term outlook remains positive, with a continued focus on portfolio growth and enhancing the store experience.

Star Supermarket Update

Trent’s Star supermarket business now operates 79 stores, with own brands contributing over 74 per cent of revenues. While the company acknowledged that Star’s expansion has been slower than anticipated, it plans to accelerate store openings in the coming periods.

Apple’s second-generation AirTag is a slightly improved version of the original tracker, maintaining the same price point of $29 for a single unit and $99 for a four-pack. While some tech enthusiasts expected more after nearly five years, testing suggests the update does not fundamentally change how the device is used.

Key New Features

The latest model includes slightly better wireless range, a 50% louder chime, and the ability to use Precision Finding on an Apple Watch without needing an iPhone. Precision Finding utilizes on-screen arrows to guide users to an item’s exact spot.

Performance Improvements

The increased loudness is considered the most significant enhancement, allowing the device to be heard more clearly in noisy environments like busy restaurants or city streets. Additionally, privacy features have been updated so that both iPhone and Android users receive alerts if an unknown AirTag is found to be traveling with them. Like the original, the tracker is powered by a CR2032 coin cell battery with an estimated year-long life.

Limitations

Despite the range improvements, the AirTag still lacks GPS and on-demand location reporting, making it significantly less useful in rural or wilderness areas compared to dense cities where Apple devices are constantly nearby. Because of these gaps in connectivity, Apple continues to emphasize that the device is intended exclusively for tracking objects, rather than people or pets.

For a gadget meant to be attached to an item and mostly forgotten until needed, the second-generation AirTag is a better version of a proven tool, but it is not considered "upgrade-worthy" for existing users.

Budget 2026 has brought borrowing concerns to the forefront of India’s financial markets, as the government’s plan to raise ₹17.2 lakh crore through dated securities is higher than anticipated. This elevated borrowing is expected to weigh heavily on the bond market, potentially pushing 10-year Government Security (G-Sec) yields up by another 5-10 basis points, which tightens financial conditions even as the RBI seeks to stimulate the economy.

Breakdown in Monetary Transmission

While central banking theory suggests that RBI rate cuts should lead to lower funding costs and cheaper borrowing, this has not happened as expected. Despite the RBI delivering 125 bps in cumulative rate cuts since early 2025, both short-term and long-term interest rates have actually risen. The G-sec yield recently hit an 11-month high of 6.72%, resulting in a steepening yield curve that signals a breakdown in monetary transmission.

Liquidity and Deposit Imbalance

The disconnect in yields is largely driven by persistent tight liquidity. Factors contributing to this include:

• Shrinking Surplus: The banking system’s liquidity surplus fell to ₹0.57 lakh crore by late January, well below the comfortable range of ₹1.5-2 lakh crore.
• Credit vs. Deposit Growth: As of December 31, the credit-to-deposit ratio hit a record 81.75%, with credit growing at 14.5% while deposits grew at only 12.7%.
• Competition for Funds: Banks are being forced to compete aggressively for deposits, which leaves less capital for government securities and pushes up short-term rates.

Additional Borrowing Pressures

Beyond the central government, States and Union Territories plan to borrow approximately ₹5 lakh crore in Q4 FY26. This surge is expected to push up State Development Loan (SDL) yields by 10-15 bps, potentially lifting corporate bond yields and further complicating monetary transmission.

External and Global Influences

External factors have added to market volatility:

• Global Jitters: Weakness in the rupee, uncertainty regarding the India-US trade deal, and delays in Indian bonds being included in Bloomberg’s Global Aggregate Index have contributed to market anxiety.
• US Treasury Yields: Despite a pivot by the US Fed, US 10-year yields have stayed above 4.2% due to fiscal deficit concerns.
• Risk Premiums: Foreign portfolio investors require a spread of at least 300-350 bps over US Treasuries to compensate for currency risk, keeping Indian yields elevated to prevent capital outflows.

The Way Forward

The persistence of these pressures suggests they are primarily structural rather than cyclical. While RBI liquidity infusions and open market operations (OMOs) offer short-term relief, they are not substitutes for stronger deposit growth, disciplined government borrowing, and credible inflation management. To restore transmission, the government must prioritize fiscal discipline and contain borrowing needs to ease pressure on the bond market.

Cooling speculation, ignoring ownership

The Budget’s decision to raise derivative STT without addressing equity cash transactions corrects excess at the top, but does little to reward behaviour at the base.

Budget 2026-27 lacked headline-grabbing reform announcements for capital markets, leading to an initially disappointed market response. While the budget enhances stability, it is questionable whether it effectively provides incentives for long-term capital accumulation.

Spot-Derivatives Imbalance

India’s capital markets have matured with increased retail participation and a shift from bank deposits to market-linked instruments, yet trading volumes and speculative leverage still outweigh genuine equity ownership. The Budget attempts to address this by raising the Securities Transaction Tax (STT) on derivatives to curb speculative activity. Specifically, STT on futures contracts has been increased to 0.05 per cent (from 0.02%), while the tax on options premium and exercise has risen to 0.15 per cent and 0.125 per cent, respectively.

While this measure is justified for financial stability, it only addresses one side of the problem. The cost of equity cash markets, which support long-term ownership, has not fallen, and STT on delivery-based trades remains the same at both entry and exit. This creates a structural bias that continues to favor frequent trading over lasting ownership.

Significant Asymmetry

A household investor building long-term wealth currently pays more in transaction taxes than a short-term trader using leveraged derivatives. This is problematic because delivery-based investing provides patient risk capital, encourages new listings, and stabilizes price discovery, whereas leveraged trading primarily provides liquidity and hedging. When systems reward financial engineering over straightforward ownership, behavior follows those incentives.

Global policies typically distinguish between speculation and investment by offering lower transaction costs or tax deferrals for long-term ownership. India’s current STT framework blurs this distinction.

Treatment of Capital Gains

A similar lack of completeness is found in long-term capital gains (LTCG) taxation. While stability in these taxes is welcome, the current regime is not especially competitive or aligned with the goal of deepening equity ownership. There remains a notable gap in incentives for longer holding periods.

If transaction costs and exit taxes stay high for delivery-based equity, households—who are encouraged to move savings from deposits to markets—may gravitate toward products offering leverage or short-term gains, which is the very behavior regulators wish to restrain.

Necessary Policy Shifts

While the Budget advances corporate bond markets and municipal bond issuance, these effects will be slow. To truly support the 2047 Viksit Bharat vision, policy must move from "cooling speculation" to "actively incentivizing ownership". Proposed solutions include:

• Restructuring STT so delivery-based transactions are taxed at significantly lower rates than derivatives or only upon exit.
• Explicitly exempting delivery-based trades while raising levies on leveraged products to align costs with economic purpose.
• Promoting holding duration through reduced tax rates for extended periods or indexation benefits to reward patience.

Conclusion

Budget 2026-27 correctly signals caution and resists excessive leverage, but capital market reforms must go beyond restraint. India's growth requires markets that simultaneously curb speculation and incentivize ownership. Until tax and transaction policies make this clear distinction, the transition from trading to investing will remain unfinished.

‘MF space to more than double in 5 yrs’

KV Kamath, Chairman of Jio Financial Services, stated that India’s mutual fund industry is expected to more than double over the next five years. This growth is projected to be driven by an economy expanding at 10 per cent annually and a massive reallocation of capital from low-interest savings accounts into higher-return investment accounts.

Current Market Dynamics

Speaking at the Jio Blackrock event, ‘Investing for a new era,’ Kamath noted that the Indian mutual fund industry currently has assets under management (AUM) of close to $900 billion. This growth has been largely powered by systematic inflows into equity schemes.

Kamath emphasized that product design and the use of technology are key drivers in attracting a new generation of participants. Notably, about one-fourth of the investors in the Jio Blackrock mutual fund are first-time investors, most of whom are investing through online modes.

A Compelling Growth Story

Kamath described India’s transformation as a process that began just four to five years ago and has created a clear pathway for the future. He expressed confidence that the country is set for at least 10 per cent year-on-year growth for the next 20 years.

Within just seven months of its launch, the Jio Blackrock Mutual Fund has already secured 1 million customers. Rob Goldstein, Chief Operating Officer at Blackrock, remarked that there are very few places in the world where such rapid growth would even be an aspiration.

Strategic Advantages

The industry views the Indian mutual fund space as being wide open for further expansion. By combining Blackrock’s global technology with the Jio brand and its extensive distribution reach, the partnership aims to deliver unique investment solutions to the Indian market.

Why are Indian IT stocks getting battered?

The Indian IT services sector faced a massive sell-off on Wednesday, February 4, 2026, with the Nifty IT index plummeting nearly 6 per cent, marking its worst performance in six years. This sharp decline followed the debut of new artificial intelligence (AI) tools that rattled technology investors worldwide.

The AI "Double Whammy"

The primary trigger for the fall was a combination of announcements from two major AI players, Palantir and Anthropic.

• Palantir: The firm reported full-year earnings and announced updates to its Hivemind AI software, granting it decision-making capabilities. Crucially, the software can now autonomously migrate data from legacy systems—a task that has long been a staple of the business for Indian IT firms.
• Anthropic: On January 30, the San Francisco-based company launched plug-ins for its Claude Cowork AI agent. These tools are designed to automate specialized tasks in marketing, legal, sales, finance, enterprise search, and customer support.

Financial Impact on Industry Giants

The launch of these AI offerings wiped off between ₹1.76 trillion and ₹2 lakh crore in market capitalization from India’s 13 largest IT services firms. Major IT stocks closed significantly lower on the day of the announcement:

• Infosys: Down 7.37% to 7.99%
• TCS: Down 6.99% to 7.01%
• Coforge: Down 7.6%
• LTIMindtree: Down 6.52%
• HCLTech: Down 4.85%
• Wipro: Down 4.51%

This negative sentiment extended to the U.S. markets, where Infosys ADR declined 5.56% and Wipro ADR fell 4.83%.

Structural and Macroeconomic Worries

Investors are increasingly concerned that advanced AI could replace a wide range of outsourced services, allowing foundation models to bypass traditional SaaS platforms and IT providers. Automation tools reduce the demand for human labor in tasks like coding, software development, and maintenance, which directly reduces the billing capacity for services-led firms.

Beyond AI, macro uncertainty has already been dampening demand for IT services. Geopolitical tensions in the Middle East and tariff fluctuations under U.S. President Donald Trump have led many Fortune 500 firms to reduce their tech spending, diverting funds instead toward their primary businesses.

Divergent Views on the Future

Analysts are currently divided on the long-term outlook for the sector:

• Jefferies expects automation to "ruin the party," predicting AI will limit IT services market growth to a 1.5-3% CAGR through 2029.
• HDFC Securities is more optimistic, suggesting the sector is positioned for a growth recovery starting in 2026 as AI eventually boosts revenue.

Industry leaders have also offered differing perspectives. Reliance Industries Chairman Mukesh Ambani sought to assuage fears, comparing the AI debut to the Industrial Revolution and calling it a "once-in-several-centuries opportunity". Conversely, TCS CEO K. Krithivasan expressed caution regarding the implementation of agentic AI, while HCLTech CEO C. Vijayakumar noted strong demand for Gen-AI being embedded into every new deal.

WHAT STATES SOUGHT AND WHAT THEY GOT

The 16th Finance Commission has finalized the distribution of the Centre’s tax revenues among states for the next five years, starting from FY27. This period marks a recalibration of the fiscal compact between the Centre and states, requiring the commission to reconcile competing demands from a diverse set of stakeholders.

Weighty Considerations and State Divergence

The commission had to balance two primary objectives: rewarding states that have controlled population growth and achieved higher income levels, while supporting those with lower per capita incomes and higher fertility rates. While there was general convergence among the 28 states on which criteria to adopt, there was significant divergence on the weightage that should be assigned to each.

For example, the per capita income distance—the markup or deficit of a state's per capita income compared to the average of the top three large states—has the highest weightage at 42.5%. While all states agreed on this criterion, their preferred weights ranged from just 15% (Haryana) to 55% (Manipur). Poorer states sought higher weightage for this factor, while economically better-off states preferred it to be lower.

Key Changes in the 16th Finance Commission’s Criteria

The commission introduced several shifts in the methodology for horizontal devolution:

• Contribution to India’s GDP: A new efficiency criterion introduced with a 10% weight to reward economic performance.
• Population (2011): The weightage was increased to 17.5% from 15%.
• Income Distance: The weight was reduced to 42.5% (from 45%) to accommodate the new efficiency criteria.
• Area: Reduced to 10% from 15%.
• Demographic Performance: Reduced to 10% from 12.5%, with the metric changing to manage aging society risks.
• Tax and Fiscal Efforts: This 2.5% weight was removed entirely, as efficiency is now captured by the GDP contribution metric.

Devolution and Impact

While many states demanded an increase to a 50% share of total tax revenues, the 16th Finance Commission has retained vertical tax devolution at 41% for the 2026–31 period.

The inclusion of the GDP contribution has lifted the shares of richer and better-performing states, such as Karnataka, Kerala, Maharashtra, and Gujarat. Conversely, some poorer states have seen marginal declines in their share of the divisible pool:

• Uttar Pradesh: Share fell from 17.9% to 17.6%.
• Bihar: Share fell from 10.1% to 9.9%.

However, even these states are expected to see an increase in the absolute amount they receive as the Centre’s tax revenues accelerate over the next five years.

A Major Policy Shift

In a significant departure from previous commissions, the 16th Finance Commission has scrapped post-devolution revenue gap grants. The panel felt that covering state deficits encourages inefficiencies and that states have sufficient room to levy additional taxes. This move is intended to curb state-level profligacy and urge states to improve tax efficiency and rationalize untargeted subsidies.

‘Subsidies can’t be rolled back abruptly, reforms will be gradual’

Expenditure Secretary V. Vualnam stated in an interview that while the government is outlining a gradual course correction for India's subsidy and spending framework, subsidies continue to serve critical national needs and cannot be withdrawn abruptly. The goal is to achieve a rationalization of these spends through constant engagement between the ministry of agriculture, the department of food and public distribution, the department of fertilizers, and the Indian Council of Agricultural Research (ICAR),.

Ensuring Food and Fertilizer Security

• Food Security: Food subsidies remain essential to guarantee food security for the poorer sections of the population across different regions, even as declining poverty levels are acknowledged. For the coming financial year, the food subsidy is estimated at ₹2.27 trillion, slightly lower than the revised estimate of ₹2.28 trillion for the current year. A major portion of this expenditure is directed toward the Pradhan Mantri Garib Kalyan Anna Yojana (PMGKAY), which provides free rations to more than 810 million beneficiaries.
• Fertilizer Availability: Fertilizer subsidies represent a firm government commitment to ensuring that farmers have adequate supplies for their crops. The projected fertilizer subsidy for the next financial year is ₹1.7 trillion, down from the revised estimate of ₹1.86 trillion for FY26. Of this, the total subsidy for urea is projected at ₹1.16 trillion, while non-urea fertilizers are allocated ₹54,000 crore.

Optimization through Technology

The government is actively exploring ways to optimize fertilizer use through data and technology due to concerns about overuse and its impact on soil health.

• Agri-Stack: Results from pilot projects using platforms like Agri-Stack in states such as Haryana and Madhya Pradesh have shown encouraging results in mapping fertilizer consumption patterns,.
• Scaling Up: These efforts will be scaled up in a step-by-step manner without diluting the core commitment to providing farmers with necessary inputs,.

The Bharat VISTAAR Initiative

Announced in the budget to bolster rural infrastructure and farm productivity, the Bharat VISTAAR initiative will be anchored by the ministry of agriculture.

• Linking Databases: The program will link AgriStack with ICAR’s knowledge databases.
• Empowering Farmers: The primary aim is to ensure farmers are better informed about the correct types and quantities of fertilizers, as well as appropriate crop choices. This is expected to enable more efficient input use over time.

Future Outlook and Strategy

Addressing concerns regarding fertilizer prices amid global geopolitical disruptions, Vualnam noted that careful planning and better targeting would help contain fiscal pressures. Additionally, the government maintains a continued emphasis on capital expenditure, as infrastructure creation has been yielding strong results for the economy.

Online ratings run into court hurdle after Chiranjeevi film

The concern is not criticism itself, which is legitimate, but distorted market signalling.

A recent court order to restrict ratings and reviews on online ticketing platforms for Telugu star Chiranjeevi’s latest film, Mana Shankara Vara Prasad Garu, has reopened a debate over whether online feedback mechanisms are shaping audience opinion or distorting it. The move, specifically aimed at platforms such as BookMyShow, highlights the need for preventive protection during a movie’s most commercially sensitive period—the window immediately surrounding its release.

Market Signalling vs. Genuine Criticism

Industry experts argue that early ratings on ticketing and aggregation platforms directly influence footfall, distributor confidence, and overall box office performance. The primary concern for the film industry is not legitimate criticism, but rather distorted market signalling. When ratings are driven by non-viewers or coordinated campaigns, they stop reflecting consumer opinion and instead become a form of reputational interference.

The court order is intended to pause or neutralize these potentially misleading signals rather than silence genuine feedback. Coordinated down-rating campaigns, fan-driven rivalries, ideological backlash, and automated activity can manipulate perception before audiences have even seen the film. In the past, major releases like Laal Singh Chaddha, Brahmastra, and Raksha Bandhan have been targets of such online trolling.

Structural Challenges and Fan Aggression

Trade experts note that fan clubs, particularly in southern India, can be extremely aggressive, making such court orders necessary to curb negative campaigning by opposing groups. Legal professionals emphasize that the purpose of these orders is to stop market manipulation, not to stifle criticism.

Platforms like IMDb and Rotten Tomatoes often face sudden bursts of low ratings within hours of a trailer release, frequently driven by bots. Currently, there is no reliable system to identify the genuineness of such ratings. While these court orders offer temporary relief, they generally stop short of addressing the deeper structural problems of the rating ecosystem.

Broader Impact and Platform Response

This issue of skewed perception through coordinated ratings extends beyond cinema to app stores, e-commerce platforms, and global content aggregators. While most platforms use moderation tools to detect abnormal spikes or flag suspicious activity, these measures are not always sufficient. Legal experts clarify that while genuine reviews constitute free speech, fake reviews or news have a significantly damaging effect.

In response to the situation, a BookMyShow spokesperson stated that the platform is law-abiding and strictly complies with all court orders. The company maintained that its audience ratings and reviews are a key part of the discovery experience and are published only from verified users who have purchased tickets through the platform and actually watched the film.

REEL CHECK

• Preventive Protection: The move signals a need for protection during a movie's most commercially sensitive moments.
• Misleading Signals: Ratings driven by non-viewers or organized campaigns fail to reflect actual consumer opinion.
• Organized Hostility: Fan rivalries and ideological backlash can heavily influence audience perception.
• Informal Ecosystem: Experts believe the largely informal ratings ecosystem can often work against the success of films.

India needs a smarter financial system rather than a bigger one

The budget’s measures to deepen market infrastructure and mobilize long-term funds could strengthen India’s bond ecosystem.

India’s budget for 2026-27 signals a growing recognition that its financial challenge is no longer one of scale alone, but of structure and effectiveness. Measures such as the introduction of a market-making framework for corporate bonds, the development of total return swaps and bond-index derivatives, incentives for large municipal bond issuances, and the creation of mechanisms such as the Infrastructure Risk Guarantee Fund and real estate investment trusts (REITs) linked to central public sector enterprises (CPSEs) point to an attempt to deepen long-term, market-based finance and improve risk distribution beyond banks. These initiatives reflect an emerging policy shift away from volume-driven credit expansion towards improving market infrastructure, liquidity, and institutional participation.

Effectiveness Over Volume

India’s economic story is often told through large reassuring numbers: trillion-dollar GDP milestones, record tax collections, and booming equity markets. Yet, for large parts of the economy, finance still does not work as it should, raising the question: Does India need a larger financial system or a more effective one?

While India’s non-financial corporate credit-to-GDP ratio remains around 55–60%, far below China’s nearly 180%, depth is not simply about the quantity of credit. What ultimately matters is how finance is structured: who receives it, at what maturity, how risks are shared, and whether savings are transformed into productive capital. India’s score on the IMF’s Financial Development Index clarifies this; while it rose from 0.12 in the early 1980s to 0.54 by 2020, the improvement was driven by efficiency and market functioning rather than sustained balance-sheet expansion. Since the mid-2010s, this momentum has slowed, and the depth of financial institutions has stagnated.

Structural Imbalances

Household balance sheets illustrate the problem starkly: nearly 80% of Indian household wealth is concentrated in real estate and gold, with bank deposits accounting for much of the rest. The result is a paradox: India saves a great deal, but those savings do not reliably become productive investment.

Corporate finance shows a similar imbalance. Shallow corporate bond markets—which are only about 18–20% of GDP compared to 80–120% in advanced economies—force firms to rely on banks and internal accruals. This matters because bond markets provide long-term funding and risk dispersion; when they are underdeveloped, banks are forced to carry risks that should be spread across investors, making lending cycles volatile.

The Role of Institutional Investors

The sharpest contrast with mature systems lies in institutional investors. Pension and insurance assets in India amount to less than 30% of GDP, whereas in countries like Canada or the Netherlands, these pools exceed 150–200%. This "patient capital" is vital for financing infrastructure and energy transitions without overwhelming banks.

The latest budget attempts to address this gap through complementary asset-creation and risk-mitigation. The Infrastructure Risk Guarantee Fund is intended to de-risk long-term lending, while recycling CPSE real estate through REITs aims to expand the supply of stable, yield-generating instruments suited to institutional portfolios.

Transactional vs. Balance-Sheet Liquidity

India has excelled at transactional liquidity; digital payments have transformed daily life into a near-frictionless public utility. However, balance-sheet liquidity—the capacity to absorb and distribute risk—remains thin. In mature systems, shocks are cushioned across banks, bondholders, insurers, and pension funds. In India, risk still flows back to banks and the sovereign, which is why credit booms are often followed by painful clean-ups.

The budget's measures aim to deepen market infrastructure and channel long-term funds into infrastructure and real estate, which should strengthen the broader bond-based financing ecosystem.

Saumitra Bhaduri is a professor at the Madras School of Economics.

OECD Economic Survey : Chile

 The sources indicate that Chile’s economy has largely resolved the macroeconomic imbalances built during the pandemic, returning to trend growth with inflation on a rapid downward path. However, fiscal space is limited, and long-term spending pressures from population ageing and the green and digital transitions necessitate a focus on fiscal sustainability and increased revenue.

Macroeconomic Outlook and Monetary Policy

• Economic Growth: GDP growth moderated to 0.3% in 2023 but is projected to recover to 2.4% in 2024, 2.3% in 2025, and 2.1% in 2026. This recovery is supported by recovering real wages and the easing of monetary policy.
• Inflation Control: Headline inflation fell from a peak of 14.1% in August 2022 to 4.2% in November 2024. Inflation expectations remain firmly anchored at the central bank’s 3% target, allowing for a gradual, data-driven easing of the policy rate, which reached 5.0% in December 2024.
• External Accounts: The current account deficit narrowed to 3.4% of GDP in 2023, financed primarily by net foreign direct investment and government debt issuance.

Fiscal Policy and Sustainability

• Fiscal Consolidation: The government is committed to fiscal responsibility, having implemented a significant adjustment in 2022 that resulted in a 1.1% surplus. Plans for 2024-2026 project a gradual consolidation, targeting a headline deficit of just 0.3% of GDP by 2026.
• Strengthened Framework: In 2024, Chile reinforced its fiscal rule by adopting a dual-target system. This includes the traditional structural balance target and a new prudent gross debt ceiling of 45% of GDP to better contain debt growth.
• Sovereign Wealth Funds: While the Economic and Social Stabilisation Fund (ESSF) provided a crucial buffer during the pandemic, its assets dropped from 5.2% of GDP in 2018 to 1.9% in 2023. The sources recommend a gradual replenishment of these funds.

Tax Reform and Revenue Mobilization

The sources emphasize that Chile’s current tax-to-GDP ratio of 21% is insufficient to meet increasing social and investment demands.

• Pact for Growth: This agenda pledges to increase permanent spending only if structural revenue increases. It aims to raise revenues by 2.1% of GDP by 2028 through measures like the recently approved Tax Compliance Law (targeting 1.5% of GDP) and efficiency gains.
• Proposed Reforms: A comprehensive tax reform is recommended to increase progressivity by raising more from personal income taxes, which currently apply to only 20% of formal workers. Conversely, the sources support lowering the corporate tax rate from 27% to 25% to spur investment.
• Resource Revenues: Chile is leveraging its natural wealth, with a new mining royalty expected to raise 0.45% of GDP annually. The fiscal rule was also adjusted in 2023 to ensure that windfall gains from lithium lease contracts are saved rather than used for permanent spending.

Structural Challenges

• Pension Reform: This remains a priority to address low replacement rates and old-age poverty. The proposed reform involves increasing employer contributions by 6% and raising the minimum guaranteed universal pension.
• Financial Market Depth: The capital market was structurally weakened by extraordinary pension withdrawals of roughly 20% of GDP during the pandemic. Future policy must avoid further withdrawals to preserve the financial system's capacity to absorb shocks.

In the context of the OECD Economic Survey: Chile 2025, fostering gender equality in the labour market is identified as a critical lever for boosting the country's potential growth and alleviating the demographic pressures of an ageing population. While gender inequalities have declined, significant gaps persist in participation, earnings, and pension benefits.

Current State of Labour Participation

Chile's female labour force participation rate reached 60.5% in 2023, a recovery from pandemic lows, but it remains significantly below the male participation rate of 77.6% and below the OECD average. These disparities are most pronounced among older cohorts; for instance, the participation gap for women aged 55–65 is 35 percentage points compared to 21 points for those aged 25–54.

The sources emphasize that closing these gender gaps is not just a matter of equity but of economic necessity. Fully closing participation and hours-worked gaps by 2060 could increase Chile's potential GDP per capita by more than 0.25 points annually.

Key Barriers to Women’s Participation

Women in Chile continue to face structural barriers that hinder their full-time integration into the workforce:

• Uneven Care Responsibilities: Women perform between 2.2 and 2.8 times as much unpaid domestic and care work as men. 35% of women outside the labour market cite domestic and care responsibilities as their primary reason for not seeking employment, compared to only 3.7% of men.
• The "Sala Cuna" Rule: Current regulations mandate that firms with more than 20 female employees provide childcare. This has inadvertently created a disincentive for firms to hire women beyond that threshold and has negatively impacted women’s salaries in larger companies.
• Motherhood Penalty: Maternal employment rates in Chile (60%) are much lower than the OECD average (71%), particularly for mothers with young children. Childbirth often leads to career breaks that result in significant long-term earnings shortfalls and lower job quality.

Earnings and Pension Gaps

The cumulative effect of these barriers results in substantial financial disparities:

• Wage Gap: The median wage gap for full-time employees is 15.4%, higher than the OECD average of 11.5%. This is exacerbated by occupational segregation, where women are concentrated in lower-paying service sectors.
• Pension Gap: Women’s pension benefits are 29% lower than men’s. This is due to lower wages, shorter contribution periods, a lower legal retirement age (60 for women vs. 65 for men), and longer life expectancy.

Skills and the Green/Digital Transition

A major challenge for future equality is the STEM gap. Only 10% of women entering tertiary education in Chile choose STEM programmes, one of the lowest rates in the OECD, compared to 47% of men. This disparity limits women's ability to benefit from high-paying roles in the digital and green transitions.

Policy Recommendations and Recent Reforms

The government has introduced several initiatives to address these issues:

• Sala Cuna para Chile Bill: A proposed reform to expand childcare to all formal workers regardless of firm size, co-financed by employer and government contributions.
• STEM Initiatives: The "Más Mujeres Científicas" policy offers additional university slots specifically for women in STEM careers.
• Leadership and Pay: New bills aim to mandate 40% gender quotas on corporate boards and require large firms to disclose gender wage gaps and establish equity plans.
• Work-Life Balance: Recent modifications to the Labour Code have reduced the work week from 45 to 40 hours and introduced teleworking rights for caregivers of children under 14.

According to the sources, Chile’s ability to accelerate productivity and boost its long-term growth potential depends heavily on its success in digitalisation and innovation. While the country has achieved high connectivity rates compared to its regional peers, it continues to lag behind the OECD average in digital skills, R&D investment, and the adoption of advanced digital tools among small firms.

Digital Infrastructure and Connectivity

Chile has made significant progress in digital infrastructure, with fibre optic connections representing roughly 69% of fixed broadband, well above the OECD average. Mobile broadband penetration and international cable installations have also expanded, positioning the country as a regional data centre hub. However, significant barriers to entry remain in the telecommunications sector due to cumbersome concession regulations. Furthermore, a digital divide persists: internet access is lower in rural areas and among low-income households compared to urban and high-income groups.

The Digital Skills Gap

A major structural barrier is the shortage of high-skilled workers for the digital transition. The sources highlight several critical skill deficiencies:

• Foundational Skills: PISA results show that literacy and numeracy skills among Chilean students are low.
• Adult Proficiency: Only 11.7% of adults in Chile are proficient in problem-solving in technology-rich environments, compared to the OECD average of 32.3%.
• ICT Shortages: There is a significant deficit of ICT professionals, with demand for cybersecurity specialists growing 10 times faster than other professions in 2022.
• Gender Disparities: Female enrollment in tertiary STEM programs is just 10%, one of the lowest rates in the OECD.

Innovation and R&D

Chile’s investment in innovation remains a weakness. Gross R&D expenditure is only 0.3% of GDP, far below the OECD average of 2.1%. Business spending on R&D is particularly low, and collaboration between firms and universities is limited. The sources note that public support for innovation is currently complex and fragmented, with overlapping objectives across different government agencies.

Adoption in the Private and Public Sectors

Digital diffusion is uneven across the economy:

• SMEs: Small and medium-sized enterprises lag significantly behind large firms in digital maturity and training. While programs like Digitaliza tu Pyme exist, they often focus on basic rather than advanced digital skills.
• FinTech: Chile has a thriving FinTech ecosystem, and the 2023 FinTech Law provides a much-needed regulatory framework to promote competition and financial inclusion.
• Digital Government: While 89% of government procedures are digitalised, public information systems remain fragmented. A unified public sector data strategy is needed to improve interoperability and service delivery.

Emerging Technologies and Security

• Artificial Intelligence: Chile updated its National AI Strategy in 2024, focusing on ethical deployment, state capacity, and talent development. AI use is rising rapidly in large firms and the public sector.
• Cybersecurity: In response to rising cyberattacks, Chile approved a new Law on Cybersecurity and Critical Information Infrastructure in 2023 to regulate essential services and enhance national digital security.

The sources characterize Chile’s green transition as a dual challenge: the country must meet ambitious decarbonization targets while simultaneously leveraging its unique natural resources to foster economic growth. Chile has a legally binding commitment to reach net-zero greenhouse gas (GHG) emissions by 2050, with emissions projected to peak in 2025. However, the sources warn that current efforts may be insufficient to meet 2030 targets, necessitating faster emissions reductions in the energy and transport sectors.

Clean Energy and Green Hydrogen

A centerpiece of Chile’s strategy is the shift toward renewable energy and the development of a green hydrogen industry.

• Renewable Energy: Solar and wind generation grew from 1% to 31% of total electricity in a decade. The government aims for 80% renewable electricity by 2030 and 100% by 2050. A major hurdle is the lack of transmission lines to move power from renewable-rich zones to demand centers, which results in wasted energy.
• Green Hydrogen: This industry is expected to contribute 21% of total GHG reductions by 2050. While Chile has significant cost advantages, the sources note that realizing this potential requires massive investment (estimated at $75 billion to reach 2030 goals), improved port infrastructure, and streamlined permitting.

Critical Minerals: Lithium and Copper

Chile’s vast reserves of lithium and copper are essential for the global energy transition, particularly for electrification and batteries.

• Production Advantage: Chile holds the world's largest share of known lithium reserves and has the lowest production costs globally.
• Environmental Trade-offs: Lithium extraction is highly water-intensive and occurs in extremely dry regions. The sources emphasize that increasing production must be balanced with protecting water availability and biodiversity in fragile Andean salt flats.
• State Participation: The National Lithium Strategy foresees significant state participation through partnerships between private firms and state-owned companies like Codelco.

Fiscal and Regulatory Reforms

To achieve these goals, the sources recommend several economic and policy shifts:

• Carbon Pricing: The current carbon tax of $5 per tonne of CO2 is considered too low to significantly alter behavior, especially compared to the government's estimated social cost of carbon ($63.4).
• Fossil Fuel Subsidies: The sources advocate for phasing out tax expenditures that support fossil fuels, such as the lower excise tax for diesel compared to gasoline.
• Permitting Reform: Lengthy and complex permitting processes—sometimes exceeding legal timeframes—are a major barrier to green investment. The proposed Sectoral Authorisations bill aims to cut approval times by one-third.

Climate Adaptation and Resilience

As one of the countries most vulnerable to climate change, Chile faces rising threats from wildfires, droughts, and floods.

• Wildfire Management: Wildfires threaten a large share of the population and jeopardize the "carbon sink" capacity of forests needed for net-zero goals.
• Infrastructure and Insurance: The sources call for increased investment in resilient infrastructure and higher take-up of home insurance, which remains low among vulnerable populations.

The "Just Transition" and Workforce

The green transition will lead to labor market shifts, particularly as coal-fired plants are phased out.

• Skill Gaps: There is a significant shortage of technicians and ICT professionals needed for the green and digital transitions.
• Support for Workers: A Just Transition strategy is being implemented to assist communities affected by coal-plant closures through reskilling programs and local economic diversification.