A Cohort Perspective on Latin America's Fertility Transition

 In the study of Latin America's fertility transition, the sources emphasize a cohort perspective, which tracks the lifetime fertility and socioeconomic outcomes of women born in the same period and place. This methodology contrasts with the more common period approach, which tracks the flow of births at specific points in time. While period measures are often used to understand real-time transitions, the cohort approach is uniquely suited for assessing theories centered on lifetime resources and decisions, such as when to leave school or how many children to have over a life course.

Data Sources and Geographic Focus

The research methodology relies on harmonized census microdata from IPUMS International, utilizing 63 censuses from 17 Spanish- and Portuguese-speaking countries in South, Central, and North America. To allow for more granular analysis, the researchers develop a panel of national and regional birth cohort aggregates. This involves tracking 333 subnational regions (typically states or provinces) to compare how within-region cohort changes in fertility relate to changes in other demographic and socioeconomic variables.

Key Methodological Innovations

• Classification by Place of Birth: A major advantage of using census data in this methodology is the ability to classify women by their place of birth rather than their place of residence. This approach is critical because it rules out potential bias stemming from selective internal migration, where individuals might move to specific areas based on fertility or education decisions.
• Temporal Matching: The cohort approach resolves the "temporal mismatch" found in period data. For instance, it ensures that socioeconomic indicators like child school enrollment rates are linked to the specific cohorts of mothers who actually have children in that age range.
• Sample Restrictions for Accuracy: To ensure the data accurately reflects completed fertility, the researchers focus on women aged 45–49, a period after childbearing is finished but before old-age mortality significantly affects the sample. For child outcomes (schooling and labor), they focus on children aged 12–15 to ensure high rates of maternal coresidence, which allows children to be linked to their mothers’ birth cohorts in the census.

Analytical Framework

The study utilizes a fixed-effect regression framework. This model relates cohort average fertility to other variables—such as mortality, education, and urbanization—while net of region fixed effects and country-by-cohort fixed effects.

• Regional Variation: The identification of trends comes from comparing cohort changes within the same region, rather than making cross-country or simple cross-sectional comparisons.
• Descriptive Nature: The authors explicitly state that their results are descriptive rather than causal. Because many factors like education and fertility may be co-determined, the methodology aims to document how these variables co-evolved rather than establishing definitive cause-and-effect relationships.
• Handling Mortality: The methodology includes a specific focus on the relationship between offspring mortality and fertility. It uses both level-on-level and log-log regression models to determine if fertility declines merely offset mortality improvements or if they outpaced them.

Limitations and Considerations

The sources acknowledge that the definition of "urban" and the scale of administrative divisions vary by country, which can limit cross-country interpretability for specific variables like urbanization. Additionally, while census data is expansive, it may lack certain granular details found in other sources, such as the specific age at marriage. Finally, to maintain precision, the methodology discards any regional cohort cells with fewer than 100 observations.

The sources identify several key demographic and socioeconomic drivers of Latin America's fertility transition, emphasizing that while many factors played a role, women's education and industrialization were the most significant predictors of the decline,.

Dominant Drivers: Education and Industrialization

• Women’s Education: This is cited as the most powerful force in the transition. Gains in women's educational attainment account for 39% of the decline in children ever born and 58% of the decline in surviving children,,.
• Husbands’ Education: While less influential than women's education, rising educational levels for husbands accounted for an additional 9–13% of the fertility decline,.
• Structural Transformation: The shift from agricultural to non-agricultural work—industrialization—accounted for approximately 5–6% of the decline,,. This factor is closely linked with the economic value of children, which tends to be higher in agricultural settings.

Mortality and Survival

A critical demographic driver was the decline in offspring mortality. The research indicates that fertility responses essentially offset improvements in child survival:

• One-for-One Offset: As mortality rates fell, the number of "children ever born" fell at a nearly identical rate,.
• Net vs. Gross Fertility: Because parents were adjusting their birth rates to keep up with mortality decline rather than overshooting it, the number of surviving children did not fall as sharply as the total number of births,,. This suggests that parents focused on reaching a target number of surviving children.

Urbanization and Migration

• Urban Living: Increased urbanization was a predictor of lower fertility in simple models,. However, the sources note that once education and industrialization are accounted for, urbanization loses much of its independent explanatory power. This is partly due to the high correlation between living in a city and working in the non-agricultural sector,.
• Migration: While many women lived outside their birth regions, migration levels were relatively stable across cohorts and were not a primary driver of the broader fertility transition,.

Women’s Employment and Marriage

• Labor Force Participation: Surprisingly, while women’s employment quadrupled across the studied cohorts, it had no residual association with fertility decline once other covariates were adjusted,,. This challenges traditional theories that suggest the "opportunity cost" of a woman's time (specifically entering the workforce) is a primary driver of lower fertility,.
• Nuptiality: The share of women who never married rose only slightly (from 12% to 15% across cohorts). While non-marriage is associated with lower fertility, this demographic shift was too small to be a major driver of the continent-wide transition,.

Challenging the "Quantity-Quality" Tradeoff

One of the most unexpected findings in the sources is that fertility decline was not systematically linked to improvements in child outcomes, such as school enrollment, literacy, or primary completion,,. While these outcomes improved across Latin America, the timing and location of these gains did not track with regional fertility declines. This challenges the popular "quantity-quality" theory, which posits that parents choose to have fewer children specifically to invest more in the education and well-being of each child,,.

In the context of Latin America’s fertility transition, the sources identify women’s education and industrialization (the shift to the non-agricultural sector) as the most powerful socioeconomic predictors of declining fertility. While several other factors—such as urbanization and women's employment—initially appear to be strong correlates, their influence often diminishes once researchers adjust for these dominant forces.

The Dominant Predictors: Education and Sectoral Shift

• Women’s Education: This is the single most significant predictor. Gains in women's schooling account for 39% of the decline in "children ever born" and 58% of the decline in surviving children across the studied cohorts. Education is thought to affect fertility through various mechanisms, including the opportunity cost of time, increased autonomy, and shifting attitudes toward family size.
• Husbands’ Education: The rising educational attainment of men also played a role, accounting for approximately 9–13% of the fertility decline.
• Industrialization: The structural transformation of the economy—specifically husbands moving from agricultural to non-agricultural work—explains roughly 5–6% of the decline. This shift is significant because the economic value of child labor is traditionally higher in agricultural settings.

Surprising Null Results and Complex Associations

The sources highlight several findings that challenge traditional economic theories of fertility:

• Women’s Employment: Although the share of women in the labor force quadrupled across the 1920–1970 cohorts, this increase had no residual association with fertility decline once education and other covariates were adjusted. This challenges theories suggesting that the "opportunity cost" of a woman's time in the workforce is a primary driver of the transition.
• Urbanization: While urbanization is a well-known predictor of lower fertility, the sources indicate it loses its independent explanatory power when industrialization (sectoral composition) is included in the model. This suggests that the rise of industrialized cities, rather than just population density, drove the change.
• Multigenerational Living: Increases in maternal coresidence (living with one's own mother) were initially associated with lower fertility. However, further analysis showed this was largely because these women were more likely to be highly educated or never married, rather than the living arrangement itself being a direct driver of lower fertility.

The "Quantity-Quality" Paradox

The sources find a notable lack of evidence for the "quantity-quality" tradeoff at the regional cohort level. While children’s school enrollment, literacy, and primary completion rates improved dramatically across Latin America, these gains did not systematically track with regional fertility declines. This suggests that while fertility was falling and education was rising, the two processes were not as tightly linked in timing and location as theories of parental investment would predict.

Summary of Predictors

Predictor	Contribution to Fertility Decline	Significance
Women's Education	39% (CEB) / 58% (Surviving)	Dominant force
Husbands' Education	9–13%	Secondary force
Non-Agricultural Work	5–6%	Consistent contributor
Women's Employment	None (after adjustment)	Challenges standard theory
Urbanization	None (after adjustment)	Linked to sectoral shift
Never Marriage	< 2%	Small quantitative impact

One of the most surprising findings in the sources is that Latin America's fertility decline was not systematically linked to improvements in child outcomes, such as school enrollment, literacy, or primary completion. While child outcomes improved significantly across the continent, these gains did not track with regional fertility declines over time.

Improvements Across Cohorts

Across the successive cohorts studied (from mothers born in the 1920s to the 1970s), there were dramatic secular improvements in the human capital of children aged 12–15:

• School Enrollment: Rose from 65% to 89%.
• Literacy: Increased from 83% to 94%.
• Primary Completion: Increased from 41% to 68%.
• Child Labor: The prevalence of work fell from 15% to 8%.

The Lack of Systematic Linkage

Despite these broad improvements, the researchers found that within specific subnational regions, the timing and location of fertility decline did not coincide with the timing and location of improvements in child schooling or work. Specifically:

• Children Ever Born: Had no significant association with school enrollment, literacy, or work in the within-region cohort analysis.
• Surviving Children: Similarly failed to predict variation in school enrollment and work.
• Literacy Paradox: In some models, surviving fertility actually showed a positive association with literacy, the opposite of what standard theories would predict.

Challenging the "Quantity-Quality" Trade-off

These findings challenge the well-known "quantity-quality" (Q-Q) theory, which posits that as parents have fewer children, they invest more in the education and well-being of each child.

• Cross-Sectional vs. Cohort Analysis: The sources note that while there is a strong negative association between family size and schooling in cross-sectional data (comparing different regions at one point in time), this relationship disappears in the regional cohort panel. This suggests that the correlation seen in cross-sectional data is likely driven by other regional factors rather than a direct trade-off between fertility and child investment.
• Broader Context: This result aligns with other recent research, such as a study in Brazil showing that twin births (which unexpectedly increase family size) do not necessarily reduce the schooling of siblings. It also echoes findings from sub-Saharan Africa, where fertility decline has been linked to the education of the mother but not to improvements in the education of her children.

In summary, while Latin American children became much more educated as fertility fell, the sources conclude that fertility decline itself was not a primary driver of these educational gains.

The sources provide a rigorous evaluation of established demographic and economic theories by applying a cohort perspective to Latin America's fertility transition. By tracking lifetime outcomes of women born between the 1920s and 1970s, the research identifies which theoretical frameworks are supported by the regional data and which are challenged.

Theories Challenged by the Data

The study finds little evidence for several prominent theories that have long been used to explain fertility decline:

• Women’s Market Work and Opportunity Cost: Theories proposed by researchers like Schultz (1985, 1997, 2007) emphasize that the rising opportunity cost of a woman’s time—driven by entering the labor force—is a primary driver of lower fertility. However, the sources show that while women's employment in Latin America quadrupled, it had no residual association with fertility decline once other factors were adjusted. This suggests that if opportunity costs mattered, they operated on the intensive margin (hours worked) or through wages rather than the extensive margin of simply being employed.
• The "Quantity-Quality" (Q-Q) Trade-off: Established by Becker and Lewis (1973), Willis (1973), and Caldwell (1980), this theory posits that parents choose to have fewer children (quantity) to invest more heavily in the human capital (quality) of each child. The sources find this theory's support "thin" in the Latin American context: fertility decline at the regional level was not systematically linked to improvements in child outcomes like school enrollment or literacy. While both trends occurred, they did not track each other in timing or location within subnational regions.

Theories Supported by the Data

Conversely, the findings provide strong empirical backing for other theoretical frameworks:

• Women’s Education as a Fundamental Determinant: The data strongly support theories emphasizing women's educational attainment as the most critical factor. Gains in education accounted for 39% of the decline in total births and 58% of the decline in surviving children. This confirms one of demography’s most "durable findings" during this historic transition.
• Structural Transformation (Industrialization): Theories linking fertility decline to the shift from agricultural to non-agricultural work are supported. The transition away from agriculture—where children often have higher economic value for labor—accounted for 5–6% of the fertility decline.
• Mortality Replacement vs. "Hoarding": The research evaluates how parents respond to falling child mortality. It finds that fertility fell "one-for-one" with mortality decline, meaning parents reduced births just enough to offset improved survival. This supports theories of replacement (bearing fewer children because more survive) but challenges theories of "hoarding" (bearing extra children as a hedge against future mortality risk), which would have predicted a sharper drop in surviving fertility.

Methodological Contributions to Theory

The authors argue that a cohort lens is superior for theoretical evaluation because many theories of the fertility transition are centered on lifetime resources and decisions. While period-based data is often used for real-time tracking, it can create a "temporal mismatch"—for example, linking current birth rates to current school enrollment rates for children who belong to entirely different maternal cohorts. By resolving this mismatch, the cohort approach provides a more accurate evidentiary base for assessing whether theories of lifetime fertility actually hold true in practice.

Supervisory Effectiveness in Mitigating Bank Commercial Real Estate Risk

 The Single Supervisory Mechanism (SSM) serves as the institutional foundation for the prudential supervision of significant institutions within the European banking union. Operating under a risk-based approach, the SSM aligns its supervisory intensity with each bank’s individual risk profile and the European Central Bank's (ECB) strategic priorities. These priorities are translated into action through the annual Supervisory Examination Programme (SEP).

CRE as a Supervisory Priority

In 2021, while establishing its 2022–2024 cycle, the ECB designated commercial real estate (CRE) as a key supervisory vulnerability. This prioritization was driven by several factors:

• Post-pandemic structural shifts: Changes in demand, such as the rise of remote work and e-commerce, have pressured office and retail property markets.
• Macro-financial risks: Rising interest rates, declining property valuations, and regulatory changes related to the green transition have increased financial pressure on banks with large CRE portfolios.
• Systemic vulnerability: Sharp price corrections in the CRE sector (approximately 16.2% between 2022 Q2 and 2024 Q1) intensified concerns that mispriced exposures could transmit stress across the financial system.

Primary Supervisory Tools

To address these risks, the SSM deployed two of its most intensive supervisory instruments, which are designed to be complementary and mutually reinforcing:

1. On-Site Inspections (OSIs): These are the most intrusive and resource-demanding tools, conducted by dedicated teams independent of regular line supervisors. They involve a multi-phase process—preparation, on-site fieldwork, reporting, and follow-up—to provide an in-depth assessment of a bank’s risk profile, internal controls, and governance. During 2021–2022, 22 significant institutions underwent CRE-focused OSIs using a harmonized methodological framework to ensure comparability across the banking union.
2. Targeted Reviews (TRs): These are off-site, thematic exercises conducted by line supervisors to benchmark practices across institutions. TRs are less intrusive but can be applied more widely to identify emerging vulnerabilities at an early stage. The 2021 CRE TR focused on how well banks were prepared for deteriorating market conditions, particularly in the office and retail segments.

Effectiveness in Mitigating Risk

The institutional context emphasizes that regulation alone is insufficient to safeguard financial stability; it must be complemented by supervisory judgment and timely intervention to prevent the build-up of vulnerabilities. Supervisory effectiveness is defined as the ability to promote safety and soundness by promptly assessing risks, identifying shortcomings, and ensuring timely remediation.

The sources indicate that while OSIs are more effective at driving durable, persistent improvements in provisioning and risk management due to their intrusive nature and binding remedial actions, TRs provide an agile, broader reach that supports early detection of risks across a wider set of banks. Collectively, this balanced combination of tools enhances the overall effectiveness of supervision in the CRE segment.

The sources identify two primary supervisory instruments deployed by the Single Supervisory Mechanism (SSM) to mitigate commercial real estate (CRE) risk: On-Site Inspections (OSIs) and Targeted Reviews (TRs). These instruments are designed to be complementary, balancing depth and intrusiveness with breadth and agility to enhance overall supervisory effectiveness.

On-Site Inspections (OSIs): Depth and Persistence

OSIs are characterized as the most intrusive and resource-demanding supervisory tool. They are conducted by dedicated teams independent of regular line supervisors and involve a rigorous four-phase process: preparation, fieldwork, reporting, and follow-up.

• Impact on Risk Mitigation: OSIs lead to persistent and economically significant increases in bank coverage ratios—the ratio of provisions to non-performing CRE loans. The sources find that these effects begin in the quarter of intervention and last for at least eight to nine quarters.
• Mechanism of Effectiveness: The effectiveness of OSIs stems from their ability to conduct in-depth assessments of internal controls and governance. They typically result in binding remedial actions and more severe measures; over 60% of OSI measures were classified as high or very high severity. These inspections often target quantitative areas such as collateral valuation, rating models, and loan-loss provisioning.
• Role: OSIs are best suited for anchoring long-term behavioral adjustments and securing durable improvements in risk management.

Targeted Reviews (TRs): Breadth and Agility

In contrast to OSIs, TRs are off-site, desk-based exercises designed to benchmark practices across a wider set of institutions. They focus on identifying emerging vulnerabilities and systemic weaknesses in specific priority areas, such as the office and retail CRE segments.

• Impact on Risk Mitigation: TRs are associated with immediate but transient improvements in coverage ratios. While they elicit a quicker reaction from banks than OSIs, their effects typically dissipate after only two quarters.
• Mechanism of Effectiveness: TRs serve a signaling and benchmarking role, allowing supervisors to spot outliers and data gaps. However, they generally result in fewer and less severe measures than OSIs, with over 70% of TR measures classified as low or moderate severity. TRs focus more on qualitative aspects like governance, strategy, and risk monitoring.
• Role: TRs are effective for broadening supervisory reach and supporting the early detection of risks across the banking union.

Complementarity and Overall Effectiveness

The larger context of supervisory effectiveness suggests that regulation alone is insufficient; it must be supported by supervisory judgment and timely intervention. The sources argue that a "balanced combination" of these two instruments is essential for mitigating CRE risk.

• The Coverage Ratio as a Metric: Effectiveness is measured by changes in the CRE-specific coverage ratio, which links asset quality to a bank’s loss-absorption capacity. Improvements in this ratio indicate stronger risk recognition induced by supervisory activities.
• Strategic Synergy: By utilizing TRs for wide-scale diagnosis and early warning, and OSIs for deep-dive remediation and enforcement, the SSM can effectively manage the "will and ability to act" necessary to prevent sectoral vulnerabilities from crystallizing into material losses.

The sources outline a rigorous empirical methodology designed to measure the effectiveness of the Single Supervisory Mechanism's (SSM) activities in mitigating commercial real estate (CRE) risk. The core of this methodology is a Difference-in-Differences (DiD) framework, utilized to evaluate how specific supervisory interventions—On-Site Inspections (OSIs) and Targeted Reviews (TRs)—influenced bank behavior.

The Outcome Variable: CRE Coverage Ratio

To measure supervisory effectiveness, the study uses the CRE-specific coverage ratio as its primary outcome variable. This ratio is defined as CRE loan-loss reserves divided by non-performing CRE loans.

• Why this metric? It is considered an informative, forward-looking indicator that directly links asset quality to a bank’s ability to absorb losses.
• Prudential Alignment: Because supervisory activities often target loan-loss provisioning and collateral management, this metric is directly aligned with supervisory priorities.
• Data Source: The analysis utilizes quarterly confidential supervisory data (FINREP and IMAS) for 81 significant institutions in the euro area between 2020 and 2024.

Difference-in-Differences (DiD) Framework

The methodology employs two distinct DiD approaches to account for the different natures of the supervisory interventions:

1. Standard Two-Way Fixed Effects (TWFE) for TRs: Because the Targeted Review was implemented simultaneously across institutions in 2022 Q3, a standard DiD model was used to compare treated banks against a control group of banks not subject to either campaign.
2. Staggered DiD for OSIs: Since the timing of on-site inspections varied by institution (staggered), the researchers applied the Sun and Abraham (2021) approach. This specialized methodology addresses potential biases in standard TWFE estimators that occur when previously treated units are used as controls for later-treated units.

Static vs. Dynamic Specifications

The methodology uses both static and dynamic models to provide a comprehensive view of effectiveness:

• Static Models: These estimate the average treatment effect following an intervention to see if, on average, the activity led to more conservative provisioning.
• Dynamic Models (Event-Study): These trace the quarterly evolution of the impact. This design is critical for assessing persistence (how long the effect lasts) and timing (whether the effect is immediate or gradual).

Identification and Robustness

The validity of the results hinges on several methodological safeguards:

• Parallel-Trends Assumption: The researchers confirm that prior to intervention, treated and untreated banks showed comparable trajectories in their coverage ratios, suggesting the results are not driven by pre-existing trends.
• Fixed Effects and Controls: The models include bank fixed effects (to capture unobserved risk appetite) and time fixed effects (to control for macro-shocks). They also incorporate lagged bank-level indicators (like CET1 and ROA) and country-level macroeconomic controls (like GDP growth and CRE price indices).
• Conditional Associations: The authors note that because supervisory interventions are risk-based rather than random, the results should be interpreted as robust conditional associations rather than definitive causal effects.

Contextualizing Effectiveness

Ultimately, the methodology allows the researchers to conclude that the effectiveness of these tools varies by instrument. For instance, the dynamic specification revealed that while TRs elicit an immediate but short-lived reaction, OSIs drive durable, persistent improvements in risk-recognition that last for over eight quarters. This empirical evidence supports the idea that a balanced combination of intrusive (OSI) and agile (TR) tools is necessary for effective supervision.

The key findings from the sources indicate that supervisory activities are effective in strengthening banks' resilience to commercial real estate (CRE) risks, though the impact and duration of this effectiveness depend heavily on the specific instrument used. The research identifies a clear distinction between the outcomes of On-Site Inspections (OSIs) and Targeted Reviews (TRs) in terms of their ability to influence bank provisioning behavior.

Effectiveness of On-Site Inspections (OSIs)

OSIs are found to be highly effective at driving durable and economically significant improvements in risk management.

• Persistence of Impact: The analysis shows that OSIs lead to a persistent increase in CRE-specific coverage ratios—the ratio of provisions to non-performing exposures—that lasts for at least eight to nine quarters.
• Magnitude: Static estimates suggest that OSIs result in an average increase in the coverage ratio of approximately 12 to 14 percentage points after accounting for bank-specific characteristics.
• Behavioral Adjustment: Because OSIs are intrusive and result in binding remedial actions, they are well-suited for anchoring long-term behavioral changes. The effects tend to strengthen over time as banks formalize findings and implement mandated corrective measures.

Effectiveness of Targeted Reviews (TRs)

In contrast, TRs are characterized as agile but transient tools for risk mitigation.

• Immediate but Short-lived: TRs trigger an immediate upward shift in coverage ratios, which is statistically significant but typically dissipates after only two quarters.
• Diagnostic Role: The effectiveness of TRs lies in their benchmarking and signaling role; they allow supervisors to quickly identify outliers and emerging vulnerabilities across a broad set of institutions.
• Qualitative Focus: TRs generally result in fewer and less severe measures than OSIs, focusing more on governance and risk monitoring rather than the direct quantitative adjustments to provisioning often required by an OSI.

Drivers of Supervisory Success

The sources attribute the differing levels of effectiveness to three primary factors:

1. Severity of Measures: OSIs resulted in an average of 13.5 measures per bank, with over 60% classified as high or very high severity, while TRs averaged 5.1 measures per bank, with 70% being low or moderate severity.
2. Instrument Intrusiveness: The multi-stage, on-site nature of OSIs provides a level of enforceability and validation that off-site, desk-based TRs lack.
3. Thematic Focus: OSI measures are more directly linked to quantitative outcomes like collateral valuation and loan-loss provisioning, whereas TRs focus on qualitative frameworks that are less likely to produce persistent changes in coverage ratios.

Conclusion on Complementarity

The larger context of these findings suggests that regulation alone is insufficient to safeguard financial stability; it must be paired with effective supervisory intervention. The sources conclude that OSIs and TRs are mutually reinforcing: TRs provide the broad reach necessary for early detection of systemic risks, while OSIs provide the deep-dive remediation required to secure lasting improvements in bank safety and soundness.

In the context of mitigating commercial real estate (CRE) risk, the sources identify the CRE-specific coverage ratio (loan-loss reserves relative to non-performing CRE loans) as the primary metric for measuring supervisory effectiveness. This ratio is considered a robust indicator of a bank’s risk recognition and loss-absorption capacity.

According to the research, the effectiveness of supervisory activities is not uniform; rather, it is propelled by three primary drivers that differentiate the impact of On-Site Inspections (OSIs) from Targeted Reviews (TRs).

1. Mode of Application and Enforceability

The degree of intrusiveness and the legal weight of the intervention are critical drivers of how long-lasting the risk mitigation becomes.

• OSIs: These are highly intrusive, multi-stage, first-hand assessments that culminate in binding remedial actions. This enforceability ensures that banks implement formal corrective measures, leading to the durable, persistent improvements in provisioning observed over nine or more quarters.
• TRs: These are desk-based, horizontal benchmarking exercises. Because they lack the same level of on-site validation and direct enforceability as OSIs, their impact on bank behavior tends to be immediate but transient, often dissipating after only two quarters.

2. Volume and Severity of Supervisory Measures

The "intensity" of the supervisory response, measured by the number and severity of mandated actions, directly influences the magnitude of the change in a bank's coverage ratio.

• OSI Intensity: On average, OSIs resulted in 13.5 measures per bank, with over 60% classified as high or very high severity. This high volume of severe measures explains the larger peak impact (approximately 20 percentage points) on coverage ratios.
• TR Intensity: TRs generated significantly fewer actions, averaging 5.1 measures per bank, with more than 70% classified as low or moderate severity. Consequently, the peak impact of TRs was lower, reaching approximately 12 percentage points.

3. Thematic and Qualitative Focus

The specific risk areas targeted by the measures determine whether the outcome is a quantitative adjustment (like increased provisioning) or a qualitative shift in governance.

• Quantitative Focus (OSIs): OSI measures are more frequently linked to financial outcomes, specifically targeting rating models, risk classification, and loan-loss provisioning. These actions have a direct, measurable impact on the coverage ratio.
• Qualitative Focus (TRs): TR measures are more concentrated on governance, strategy, and risk monitoring frameworks. While essential for long-term health, these qualitative improvements are less likely to produce immediate or persistent changes in quantitative prudential metrics.

Strategic Complementarity

These drivers explain why the two instruments are mutually reinforcing. While the breadth and agility of TRs allow supervisors to quickly signal concerns and identify emerging vulnerabilities across the banking union, the depth and enforceability of OSIs are necessary to anchor behavioral changes and ensure systemic resilience in the CRE sector.

Climate Change and Regional Economic Growth in the EU

 This study, titled "Beat the heat, the role of heat waves and droughts in regional EU economies," provides a comprehensive analysis of how extreme climate events influence regional economic output across the European Union. Developed as part of the European Central Bank's Working Paper Series, the research aims to bridge the gap in quantifying short-term economic effects of heat waves and droughts, which are increasingly frequent and widespread in Europe.

Study Overview and Scope

The study develops climate-augmented predictive models to forecast real growth in per capita Gross Value Added (GVA) across 1,117 EU regions (at the NUTS-3 level) from 2002 to 2022. It focuses on three key sectors:

• Agriculture (Sector A).
• Industrial Aggregate (Sectors B-E, including mining, manufacturing, energy, and water supply).
• Manufacturing as a standalone sector (Sector C).

The methodology integrates traditional economic indicators with high-frequency climate data from the Copernicus European Drought Observatory, capturing dimensions such as heat waves, meteorological droughts (precipitation deficits), hydrological droughts (low river flows), and agricultural droughts (soil moisture and vegetation stress).

Context: Heat Waves and Droughts in EU Regional Economies

The sources emphasize that Europe is entering a period of compounding climate risks where extreme events like the record-breaking 2022 drought illustrate how hot and dry conditions can cascade across sectors.

• Broader Macroeconomic Impact: Evidence suggests major droughts can depress regional output by up to 3 percentage points for as long as four years after the event. Furthermore, harvest failures have significant inflationary effects, explaining roughly 30% of medium-term euro area inflation volatility.
• Sectoral Disruptions: Beyond agriculture, droughts disrupt river transport (e.g., the Rhine), curtail hydroelectric and thermal power production, and increase costs for water-dependent manufacturing.

Key Findings on Sectoral Vulnerability

The study reveals that the economic impact of these climate stressors is highly sector-dependent and operates through nonlinear channels.

• Agriculture: This is the most sensitive sector. Simulations of extreme compound events (heat and drought) suggest agricultural annual growth could fall by an average of 4.54 percentage points across most regions.
• Industry and Manufacturing: These sectors are less affected overall. The industrial aggregate experiences moderate simulated reductions (average -0.75 pp), while manufacturing remains largely stable (average -0.11 pp). This resilience is attributed to the "buffering role" of indoor production environments, which protect manufacturing from direct exposure to extreme heat and drought.

Regional Heterogeneity and Adaptive Capacity

The sources highlight a stark divide in how different EU regions respond to these climate shocks:

• Eastern Europe and the Baltic States: These regions face the most severe simulated losses in both agriculture and industry. This vulnerability is linked to a reliance on rain-fed agriculture, less developed irrigation infrastructure, and higher energy-intensity in production.
• Southern Europe: Despite being prone to chronic heat and water scarcity, this region often exhibits more muted short-term impacts in agriculture. This is attributed to higher structural adaptation, such as the widespread use of irrigation systems that can buffer initial losses.

Methodological Significance

A core conclusion of the study is that Machine Learning (ML) models (specifically Random Forest and XGBoost) significantly outperform linear models in predicting outcomes for climate-sensitive sectors. This is because ML can better capture the complex nonlinear interactions and seasonal nuances of climate shocks—such as the spatial propagation of a heat wave from a neighboring region—that traditional linear frameworks often miss.

The methodological approach described in the sources represents a shift from traditional causal inference toward predictive modeling, specifically designed to capture the localized and complex nature of climate shocks across 1,117 EU regions. By integrating high-frequency climate data with annual economic indicators, the study seeks to quantify short-term impacts that are often obscured in country-level analyses.

The core components of this approach include:

1. Spatial and Sectoral Granularity

The study operates at the NUTS-3 level, which allows researchers to account for the highly localized nature of heat waves and droughts. This granularity is essential because economic impacts vary significantly depending on a region's exposure, sectoral composition, and adaptive capacity. The analysis focuses on three specific NACE sectors:

• Agriculture (Sector A).
• Industrial Aggregate (Sectors B-E, including energy and water supply).
• Manufacturing (Sector C).

2. Machine Learning vs. Linear Benchmarks

A central finding of the methodological exercise is that nonlinear Machine Learning (ML) models—specifically Random Forest and XGBoost—consistently outperform traditional linear regression in climate-sensitive sectors.

• Nonlinear Dynamics: The sources argue that the economic effects of climate extremes operate through nonlinear channels that linear models cannot represent.
• Regularization: ML models are better equipped to handle multicollinearity, which is a frequent challenge when climate indicators (like heat and drought) are highly correlated.

3. Reconciling Data Frequencies

To bridge the gap between daily climate observations and annual economic growth data, the study utilizes three distinct feature-engineering pipelines:

• Yearly Aggregation: Summarizing daily data into annual medians and standard deviations to capture both central tendencies and volatility.
• Principal Component Analysis (PCA): Extracting singular features from climate indicators to mitigate multicollinearity.
• Mixed Data Sampling (MIDAS): Applying lag weights to monthly observations to capture the gradual onset or dissipation of extreme events. Interestingly, the study found that simple annual aggregation often performed as well as or better than more complex extraction techniques, particularly in short panels where complex models risk over-fitting.

4. Accounting for Compounding and Spillovers

The methodology specifically addresses the compounding nature of climate risks across three dimensions:

• Temporal Compounding: Incorporating event duration into severity indices.
• Geographic Compounding: Using spatial averages of climate features from neighboring regions to capture spillover effects and shared climate systems.
• Event Compounding: Creating interaction terms (specifically for heat waves and droughts) to model the unique economic impact of simultaneous stressors.

5. Model Interpretability and Simulation

To make these "black box" ML models transparent, the researchers use SHAP (SHapley Additive exPlanations) values. This technique identifies which predictors—economic or climatic—are driving the model's output without assuming a specific functional form.

Finally, the study applies its best-performing model (XGBoost with yearly aggregation) to simulate extreme scenarios, such as a repeat of the 2022 drought. These simulations provide a "stress test" for regional economies, revealing how a uniform climate shock would result in heterogeneous economic outcomes based on regional resilience and infrastructure.

The study utilizes a multifaceted set of climate indicators sourced from the Copernicus European Drought Observatory to capture the diverse dimensions of climate stress affecting EU regional economies. These indicators are essential for characterizing the intensity, duration, and spatial extent of extreme events that disrupt economic output.

Core Climate Indicators

The researchers categorized these indicators into four primary groups to reflect different environmental and economic impacts:

• Heat Waves: Measured by the Heat and Cold Waves Index (HCWI), which monitors daily minimum and maximum temperatures against 30-year climatological thresholds to identify events lasting at least three consecutive days.
• Meteorological Droughts: Captured by the Standardised Precipitation Index (SPI) across three horizons:
  • SPI01 (1-month): Indicates immediate effects such as soil moisture deficits.
  • SPI06 (6-month): Reflects deficits in streamflow and reservoir storage.
  • SPI12 (12-month): Highlights long-term reductions in groundwater and reservoir recharge.
• Hydrological Droughts: Monitored via the Low-Flow Index (LFI), which detects periods of unusually low river discharge compared to long-term thresholds.
• Agricultural Droughts: Assessed using the Soil Moisture Anomaly (SMA) and the Fraction of Absorbed Photosynthetically Active Radiation (fAPAR). SMA measures deviations in soil moisture, while fAPAR tracks anomalies in vegetation photosynthetic activity, which are critical for predicting crop stress.

Compounding and Spatial Indicators

Recognizing that climate risks rarely occur in isolation, the study developed indicators to capture compounding effects and spatial spillovers:

• Compound Events: Researchers created a specific feature to account for the simultaneous occurrence of heat waves and droughts by interacting the scaled HCWI and SPI indicators.
• Geographic Compounding: To account for the spatial propagation of climate shocks, the study incorporates regional averages of climate features from neighboring areas. This allows the models to capture how a drought or heat wave in one region might influence economic activity in another through shared ecosystems or trade routes.

Observed Trends in EU Regions

Data from these indicators reveal significant shifts in the European climate landscape over the study period (2002–2022):

• Increasing Heat Stress: Most European regions have seen a rise in the average number of annual heat wave days, with the most pronounced increases in the Spanish Mediterranean, southern Italy, and parts of northern and eastern Europe.
• Intensifying Dryness: Indicators like SPI01 and LFI suggest a trend toward increased dryness, particularly in central Europe, while agricultural drought (fAPAR) has shown significant increases in western and northern Europe over the last decade.

Sector-Specific Sensitivity

The predictive power of these indicators varies by economic sector. Agriculture is most sensitive to HCWI and short-term meteorological drought (SPI01, SPI06), which directly impact crop yields and vegetation health. In contrast, the Industrial Aggregate and Manufacturing are more influenced by hydrological and long-term drought (LFI, SPI12), which affect water-dependent processes like cooling for power plants and inland shipping.

The sources provide a detailed sectoral impact analysis of how heat waves and droughts influence 1,117 EU regional economies, focusing on three specific classifications: Agriculture (Sector A), the Industrial Aggregate (Sectors B-E, which includes mining, manufacturing, energy, and water supply), and Manufacturing (Sector C) as a standalone subset.

The analysis reveals that these extreme climate events do not affect sectors uniformly, with impacts ranging from severe disruptions to notable resilience.

1. Agriculture (Sector A): The Most Sensitive Sector

Agriculture is identified as the most vulnerable sector to climate extremes.

• Magnitude of Impact: Simulations of extreme compound heat and drought events, similar to conditions in 2022, suggest agricultural annual growth could fall by an average of 4.54 percentage points (pp) relative to a no-anomaly benchmark.
• Regional Variation: Losses are most severe in Eastern Europe (averaging -5.36 pp), particularly in regions like Romania, Bulgaria, and the Czech Republic. In contrast, Southern Europe exhibits more muted short-term impacts.
• Drivers of Vulnerability: The high sensitivity in Northern and Eastern Europe is linked to a heavy reliance on rain-fed systems and limited irrigation infrastructure. Conversely, Southern Europe’s resilience is attributed to structural adaptation, such as extensive irrigation systems that buffer initial output losses.

2. Industrial Aggregate (Sectors B-E): Moderate and Heterogeneous Effects

The broader industrial sector experience smaller but still meaningful reductions in economic output.

• Magnitude of Impact: The simulated compound event results in an average reduction of 0.75 pp in real GVA per capita growth.
• Exposure Channels: This aggregate is more affected than manufacturing alone because it includes activities with high outdoor or infrastructure-related exposure, such as extraction, utilities, and water infrastructure.
• Regional Vulnerability: Again, Eastern Europe and the Baltic states face more visible negative effects, which the sources suggest may reflect a combination of higher energy intensity, aging infrastructure, and less developed adaptive capacity.

3. Manufacturing (Sector C): A "Buffer" of Resilience

Manufacturing shows significant resilience compared to other climate-exposed sectors.

• Magnitude of Impact: Simulated losses remain broadly stable, averaging only -0.11 pp across the EU.
• Indoor Production Protection: The sources attribute this resilience to the predominance of indoor production environments, which protect labor productivity and industrial processes from the direct physical stress of extreme heat and drought.
• Economic Significance: Despite these small percentage declines, the sources note that manufacturing accounts for 16.9% of total EU GVA (compared to 1.89% for agriculture). Therefore, even minor percentage drops can translate into significant absolute economic losses.

4. Broader Context: Compounding Factors and Inflation

Beyond direct production losses, the sectoral analysis highlights several cascading economic effects:

• Energy Intensity: While manufacturing is energy-intensive, the study suggests that direct climatic exposure and sectoral sensitivity (like being outdoors) are more significant drivers of short-term GVA loss than energy-product use alone.
• Inflationary Pressures: Agricultural shocks are a major source of volatility, with harvest failures explaining roughly 30% of medium-term euro area inflation volatility.
• Supply Chain Disruptions: Droughts propagate through production networks via disruptions to river transport (e.g., the Rhine), water-dependent manufacturing, and electricity generation, which can increase costs and constrain output across multiple sectors.

The 2022 Extreme Scenario Simulation serves as a "stress test" within this study, designed to quantify how a uniform climate shock—modeled after the record-breaking heat waves and droughts of 2022—would impact economic output across diverse EU regions. Using a high-performing XGBoost model, the researchers compared a "no-anomaly" benchmark against a scenario where every region was subjected to extreme tail percentiles of climate stress (e.g., the 99th percentile for heat waves and the 1st percentile for soil moisture).

The simulation highlights a stark divide in sectoral vulnerability and regional resilience across the European economy:

Sectoral Losses: Agriculture vs. Industry

• Agriculture (Sector A): This sector faces the most devastating simulated impacts, with an average reduction in real GVA per capita growth of 4.54 percentage points (pp). In some regions, losses reached as high as 7.36 pp, illustrating the extreme sensitivity of food production to compounding heat and moisture stress.
• Industrial Aggregate (Sectors B-E): The impact on the broader industrial sector is more moderate, averaging a 0.75 pp reduction. These losses are driven by climate-sensitive infrastructure, such as water-dependent power plant cooling and extraction activities.
• Manufacturing (Sector C): This sub-sector remains remarkably stable, with an average loss of only 0.11 pp. The sources attribute this resilience to the buffering role of indoor production environments, which shield labor and processes from direct heat exposure.

Regional Heterogeneity and Adaptation

A critical finding of the 2022 simulation is that the same climatic shock produces vastly different economic outcomes based on a region's adaptive capacity:

• The Eastern European Vulnerability: Regions in Romania, Bulgaria, and the Czech Republic face the most severe losses (averaging -5.36 pp in agriculture). This is linked to a heavy reliance on rain-fed agricultural systems and less developed irrigation and water infrastructure.
• The Southern European Buffer: Despite being prone to chronic heat, regions in Italy and Greece show more muted short-term agricultural impacts (averaging -3.9 pp). This resilience is credited to structural adaptation, specifically the widespread use of irrigation systems that can temporarily offset drought conditions.

Broader Economic Context

The sources emphasize that even the "modest" percentage declines in manufacturing must be viewed through the lens of economic scale. Since manufacturing accounts for 16.9% of total EU GVA (compared to less than 2% for agriculture), even a fractional percentage drop represents economically significant absolute losses.

Ultimately, the 2022 simulation demonstrates that while the European economy has some "indoor" defenses, compounding climate risks—where heat and drought interact—can cascade through energy systems and supply chains, potentially exacerbating regional wealth disparities if adaptation infrastructure is not prioritized.

The study concludes that heat waves and droughts exert material, nonlinear, and sector-dependent influences on regional economic activity in the EU. By integrating high-frequency climate data with economic indicators, the researchers provide a framework for real-time monitoring and targeted policy interventions,.

Key Conclusions of the Study

• Predictive Value of Machine Learning (ML): A primary conclusion is that nonlinear ML models (Random Forest and XGBoost) significantly outperform traditional linear benchmarks in climate-sensitive sectors like agriculture,,. These models are better at capturing the complex, compounding nature of climate shocks—such as simultaneous heat and dryness—that linear models often miss,.
• Extreme Sectoral Sensitivity: Agriculture is the most vulnerable sector, with simulations suggesting that an extreme event like the 2022 drought can reduce annual growth in real per capita Gross Value Added (GVA) by an average of 4.54 percentage points across EU regions,.
• The "Indoor" Resilience of Manufacturing: Manufacturing shows notable resilience, with average simulated losses of only -0.11 pp,. This is attributed to the "buffering role" of indoor production environments, which shield labor and industrial processes from the direct physical stress of extreme heat,.
• Regional Wealth and Adaptation Disparities: The study finds that climate shocks exacerbate regional disparities. Eastern Europe and the Baltic states face more severe industrial and agricultural losses due to higher energy intensity and less developed irrigation,,. Conversely, Southern Europe exhibits more muted short-term agricultural impacts because of extensive structural adaptation, such as irrigation systems,.

Policy Implications and Recommendations

The sources highlight several critical avenues for policymakers to enhance regional economic resilience:

• Integration into Monitoring Tools: The findings underscore the importance of integrating high-frequency climate information into short-term economic monitoring tools used by central banks and fiscal authorities,.
• Early-Warning Systems: Improved climate-augmented modeling can underpin early-warning systems, allowing for more proactive management of upcoming climate-induced economic stress,.
• Targeted Adaptation Strategies: By identifying the specific sectors and regions most at risk, the research guides the design of targeted adaptation policies,. For instance, policymakers in Northern and Eastern Europe may need to prioritize irrigation infrastructure, while Southern Europe may need to address the "finite" nature of its current water buffering capacity.
• Regional Fiscal Planning: The models can inform regional fiscal planning, such as the allocation of contingency funds and intergovernmental transfers, to support regions hit by severe shocks.
• System-Wide Stress Testing: The sources suggest that future policy priorities should include coupling these sectoral predictions with financial-exposure data for system-wide stress testing to understand how climate shocks propagate through banking and financial systems.

Limitations and Future Directions

The researchers caution that their findings are predictive rather than causal, representing conditional associations rather than established structural parameters,. They suggest that future work should explore absolute thresholds—such as water requirements for cooling power plants—to better characterize the nonlinear impacts on manufacturing and energy-intensive industries. Additionally, the view expressed in the paper is that of the authors and does not necessarily represent the official position of the European Central Bank.

Newspaper Summary 170626

 

Tata Motors FY26 free cash flow ‘negative’ on JLR woes

Amit Vijay Mohile Mumbai

Tata Motors reported negative free cash flow of ₹26,823 crore in FY26, compared with positive free cash flow of ₹22,236 crore a year earlier, as challenges at Jaguar Land Rover (JLR) weighed heavily on the group’s finances. The company’s consolidated balance sheet moved from a net cash position of ₹1,018 crore to net debt of ₹30,710 crore, reflecting weaker cash generation at JLR and continued investment across the business.

ANNUAL REPORT

Despite the financial pressure, Tata Motors maintained a strong investment programme, committing ₹36,236 crore in capital expenditure and ₹34,562 crore in research and development during the year, according to its 81st Integrated Annual Report. The biggest drag on performance came from JLR, where a cyber incident led to a five-week production shutdown and tariff-related pressures affected key export markets.

Wholesale volumes declined 23.2 per cent year-on-year to 307,915 units, excluding the China joint venture, while revenue fell 20.9 per cent to £22.9 billion from £29 billion in FY25.

The impact was visible at the group level. Consolidated revenue stood at ₹3,35,582 crore, while profit before tax before exceptional items dropped sharply to ₹2,519 crore from ₹28,650 crore a year earlier. Even as profitability weakened, Tata Motors continued to invest in future products and technologies.

Intangible assets under development, covering vehicle programmes and technologies across JLR and Tata Motors Passenger Vehicles, rose to ₹76,154 crore as of March 31 from ₹48,182 crore a year earlier.

“Rapid global advances in digital technologies and AI are transforming how mobility products are designed, experienced and supported,” said Chairman N Chandrasekaran in his message to shareholders. He noted that clean-energy transition, safety requirements and supply-chain shifts are reshaping competitiveness in the global auto industry.

RECOVERY SIGNS

There were signs of recovery towards the end of the year. Following the resumption of production, Q4 revenue reached ₹1,05,447 crore and profit before tax before exceptional items improved to ₹7,167 crore.

While JLR struggled, Tata Motors’ domestic passenger vehicle business provided support. Revenue rose 20.7 per cent to ₹58,465 crore and profit before tax before exceptional items increased 32.6 per cent to ₹1,436 crore. Electric vehicle sales climbed 43.4 per cent to 92,179 units, helping the company retain a 40.2 per cent share of India’s EV market.

Meeting on G7 sidelines, Modi and Trump to discuss FTA, sailors’ deaths

Amiti Sen New Delhi

When US President Donald Trump meets Prime Minister Narendra Modi on the sidelines of the G7 summit in Evian, France, on Wednesday, the push for an expeditious conclusion of the India-US interim trade deal will take centre stage. However, New Delhi will still wait to ensure that sticky issues, including the US’ penal tariffs on Indian exports and India’s competitive edge over rivals, are satisfactorily addressed.

“India is in favour of an interim deal but it has to first know what the US tariffs on its goods would be. Moreover, the deal has to be such that it gives Indian exporters a guaranteed edge over competitors such as Vietnam, Bangladesh and Indonesia. The Modi-Trump meet will at best result in an exchange of good intentions on the deal,” a source tracking the matter told businessline.

KEY ISSUES Significantly, the leaders, who will meet face-to-face after 16 months, are also expected to discuss the situation in West Asia in the light of the recent killing of three Indian sailors by US forces in the Gulf of Oman and the proposed US’ deal with Iran to end the war and the Strait of Hormuz blockade. Other issues likely to be taken up include partnership in critical minerals and securing supply chains, increased trade in energy, co-operation in AI and digital infrastructure, and securing navigation.

SJM’S ANGER There is pressure on Modi from several quarters, including Opposition leaders, bodies such as the seafarers’ association and family members of the victims, to take up the matter with Trump.

Swadeshi Jagran Manch (SJM), the economic wing of the RSS (the ruling BJP’s ideological mentor), lashed out against the US action that resulted in the mariners’ deaths, in a letter to the US Ambassador to India Sergio Gor on Monday.

“These incidents have sent a wave of disbelief and anger among the people of India. US administration added insult to injury by an insensitive and irresponsible response, hurting Indian sentiments further, who had always considered US to be a great friend... It is a serious violation of the international law governing the seas, armed conflict and human rights,” wrote Ashwini Mahajan, Co-convenor, SJM.

Centre’s foodgrain reserves at a record high as El Nino threatens kharif production

Prabhudatta Mishra New Delhi

Foodgrain reserves in the Central Pool surged to a record high of 122 million tonnes (mt) as of June 1. Equal to the country’s entire annual rice consumption, this massive stockpile gives the government a critical buffer just as El Nino risks disrupting the 2026 kharif crop.

Given that the country’s free foodgrain schemes for over 80 crore beneficiaries require an annual offtake of 56 mt (based on 2025-26 data), the current reserves are sufficient to comfortably sustain these welfare programmes for at least two years.

“The stock in the Central Pool, although higher than requirement, assures the country of food security. There is no cause of concern as far as basic food availability is concerned even if the monsoon is below normal. The stocks can also be off-loaded under the open market sale scheme to bulk consumers, including State governments,” said Union Food Secretary Sanjeev Chopra.

OMSS PROGRAMME

What Chopra is saying suggests that the Centre may release grains to the States for bulk consumers under the Open Market Sale Scheme (OMSS). Despite the “below normal” monsoon forecast, at 90 per cent of the long period average, the government is targeting a kharif foodgrain production during 2026-27 of 176.16 mt, against the actual output of 176.04 mt in 2025-26.

The target for 2026-27 also includes 123.15 mt of rice, 8.4 mt of pulses, 28.92 mt of oilseeds, 13.56 mt of nutri cereals and 31.04 mt of maize.

“We may need higher allocation under OMSS also to check food inflation. So, the allocation of rice for ethanol at highly subsidised price of ₹2,320 per quintal needs to be drastically reduced from about 5.2 mt announced earlier,” said former Agriculture Secretary Siraj Hussain.

FIA backs SEBI’s options strike framework

Our Bureau Mumbai

The Futures Industry Association (FIA) has stated that SEBI’s proposal to allow exchanges to add strike prices in line with market movement will improve price discovery and risk management for participants.

“We support the proposal to introduce new strikes intra-day in the direction of price movement. This would address a long-standing operational and risk-management issue for market participants,” the FIA said in its submission to the regulator.

STRIKE PREDICTABILITY

The association, which represents clearing firms, exchanges, trading firms, and other derivatives market participants globally, noted that the framework would improve the predictability and availability of option strikes, especially during periods of heightened volatility. It added that a consistent approach across exchanges would enhance operational efficiency.

However, the FIA emphasized that the effectiveness of this framework depends on a “high degree of consistency” in implementation. It recommended that SEBI prescribe minimum common standards for:

• Strike publication timing and terminology.
• File formats and intra-day notification protocols.
• Transparency in strike addition rules.
• Uniform minimum requirements on the range and number of in-the-money (ITM) and out-of-the-money (OTM) strikes across products.

Without these standards, the FIA warned that exchange-level discretion could lead to uneven outcomes and increased operational complexity.

MARGIN EFFICIENCY

A primary concern for the association relates to existing positions. The FIA cautioned against removing or disabling strikes where open interest continues to exist, as this could force participants into inefficient exits.

“If a strike is purged, disabled, removed or otherwise made unavailable while open interest remains, participants may be left with exercise or expiry as the only practical means of exit,” the association stated.

It recommended that these strikes should remain available for trading, hedging, or closing out positions until open interest is extinguished. This approach would avoid unnecessary margin lock-ups and preserve risk management flexibility.

The FIA further suggested that intra-day strike additions be disseminated via existing automated exchange channels, such as FIX and binary market data feeds, to ensure seamless integration into trading systems without manual intervention.

Finally, the association called for an annual review mechanism for strike frameworks involving market participants and suggested that SEBI provide a reasonable transition period for implementation so that systems and processes can be properly upgraded.

‘India’s 5G subscription to reach 1.1 b by 2031’

S Ronendra Singh New Delhi

5G subscriptions are expected to reach more than 1.1 billion by the end of 2031, reaching 81 per cent subscription penetration as adoption in the country continues to grow rapidly, according to the Ericsson Mobility Report (EMR) released on Tuesday.

The growth is driven by the availability of affordable 5G-enabled smartphones and devices, expanded network coverage across almost all districts, and the increasing rollout of 5G fixed wireless access (FWA) services.

The report stated that 5G subscriptions reached 430 million at the end of 2025, accounting for 35 per cent of total mobile subscriptions. While 4G remains the dominant technology at 46 per cent, subscriptions are forecast to decline from around 570 million in 2025 to nearly 160 million by 2031 as users migrate to 5G.

GLOBAL LEAD

India continues to lead globally in mobile data consumption per smartphone, with average monthly usage already at 37 GB and expected to nearly double to 70 GB by 2031.

“India’s rapidly growing 5G adoption based on enhanced mobile broadband and 5G FWA is transforming consumer experiences. The robust and secure 5G infrastructure in the country is driving inclusion, governance and innovation at scale, and is serving as a powerful foundation for digital India,” said Nitin Bansal, Managing Director, Ericsson India.

NETWORK SLICING

In a significant development, a service provider (Bharti Airtel) in India recently launched differentiated connectivity services based on network slicing for its postpaid 5G customers, signalling the evolution of advanced 5G use cases in the market.

The June 2026 report covered the same period (2025-2031) as the November 2025 edition, but with updated statistics and forecasts. It further noted that global 5G mobile subscriptions passed the three-billion mark during the first quarter of 2026. This global figure is expected to grow rapidly and is forecast to more than double to 6.4 billion by the end of 2031.

Western Europe, North America, North-East Asia and the GCC countries are forecast to have 5G mobile subscription adoption close to, or above, 90 per cent by the end of 2031.

6G OUTLOOK

The report also touched upon the future, stating that the first implementable 6G specifications are expected to be finalised by the end of 2028 or early 2029. The first commercial 6G services are expected to follow around 2030, with the US, China, Japan, South Korea and the GCC countries expected to be early adopters.

‘Poor data quality is hurting AI ambitions’

Vallari Sanzgiri Mumbai

Low quality of data is the biggest hindrance in the enterprise leap from pilot stage AI-systems to production ready AI agents, said Anand Ramamoorthy, Director APAC Data Governance and Quality at Informatica from Salesforce, in an exclusive conversation with businessline.

Following the company’s Data and AI Summit in Mumbai on June 11, Ramamoorthy said many enterprises had voiced concern about the quality of their data, with one company flagging 73 per cent of its data as “bad”.

DATA GOVERNANCE

“Data quality is the biggest impediment to translating these agents that you’re building to make it production-ready. It’s critical to have a data governance capability. The problem is the manual effort slows things down. So, even though it’s critical, they lose patience thinking that they’re not getting the value,” said Ramamoorthy.

Despite this hurdle, Ramamoorthy pointed out that traditional data management norms expect humans to be in the loop of workflows or in the interpreting of data. This means that the context when using data needs to be set by a human that can understand nuance rather than an AI agent that is liable to hallucinate.

“Data itself is not always incorrect. It is sometimes ambiguous, depending on the usage, the interpretation can be different. So, when you apply the agents on top of that, it amplifies that problem. That can lead to hallucination, the outcomes can be different,” he said.

THREE KEY PILLARS

To address these concerns, Ramamoorthy suggested three key pillars in the world of agentic AI:

• Machine readable metadata with trusted context.
• AI-ready data products.
• AI-assisted data stewards that take up the task of providing governance policies around ownership, accountability, definitions, etc.

“It’s about how do we unlock the value of these data stewards who are good at functional and business-oriented conversations. How do we instil that into the manual effort rather than focus on mundane, repeatable manual tasks?” he said.

‘States’ own taxes grow to more than half of total revenue receipts’

Shishir Sinha New Delhi

The share of States’ own tax revenue in their revenue receipts grew to over 50 per cent during FY25 but with lower buoyancy, said the office of the Comptroller & Auditor General (CAG) in its report on State finances. Meanwhile, the States are getting more from the Centre as part of devolution.

CAG K Sanjay Murthy released the third edition of the Publication on State Finances 2024-25 on Tuesday. According to the report, States Own Tax Revenue (SOTR), the largest component of revenue receipts, increased significantly in absolute terms and its share to 50.13 per cent in FY25 from about 49.55 per cent in FY24.

However, its buoyancy — the ratio of change in tax revenue in relation to change in gross state domestic product — weakened to 0.67 in FY25 over 0.92 of FY24 and 1.43 of FY23. During FY25, the top seven States whose SOTR contributed up to 60 per cent of revenue receipts were Gujarat, Haryana, Karnataka, Kerala, Maharashtra, Tamil Nadu and Telangana. On the other hand, Arunachal Pradesh, Manipur, Mizoram, Nagaland, Sikkim and Tripura had SOTR of less than 20 per cent of their total revenue receipts. The average annual growth of SOTR of all the States combined was 11.05 per cent during the period 2018-19 to 2024-25.

UDAY IMPACT

According to the report, in FY25, capital expenditure of ₹8.49 lakh crore constituted 16.59 per cent of the total expenditure by the States, the remaining 83.41 per cent being revenue expenditure.

During the 10-year period, a spurt in share of capital expenditure was evident in FY 2015-16 and FY 2016-17. “The rise in capital expenditure during these two financial years was mainly driven by States investing in the equity of State power undertakings and by the extension of loans to power utilities, following the takeover of 75 per cent of the debt of State-owned power distribution companies by 14 State governments under the Ujwal Discom Assurance Yojana (UDAY),” the report said.

SHARE OF SUBSIDIES

On an average, capital expenditure of the States has remained in the range of 13–20 per cent of the total budgetary spending in the 10-year period of FY16 and FY25.

The report highlighted that subsidies at ₹4.37 lakh crore was one of the major components of revenue expenditure in several States. The principal subsidy outgo was to energy utilities and agriculture. The decadal trend shows that in most years the share of subsidy expenditure has been in the region of 8-10 per cent of the total revenue expenditure of all States combined.

On liabilities, as on March 31, 2025, there was a wide variation from 15.79 per cent of GSDP in case of Odisha to 52.84 per cent of GSDP in case of Arunachal Pradesh. During the period FY16 to FY25 as a percentage of GSDP, total liabilities increased to 27.89 per cent from 24.19 per cent. In FY25, all States were in fiscal deficit ranging from 1.66 per cent of GSDP in the case of Goa to 8.69 per cent in Meghalaya.

TRENDS IN STATES’ EXPENDITURE

• Committed + Subsidies + GIA Salary: ₹26.12 lakh crore (61.17% of revenue expenditure).
• Subsidy growth: Grew 214 per cent from ₹1.39 lakh crore in FY16 to ₹4.37 lakh crore in FY25.
• Growth parity: Both revenue and committed expenditure grew 137 per cent.
• Committed expenditure: 14 States had committed expenditure more than 50 per cent of their revenue expenditure.

Beyond the wage: Building a workforce for Viksit Bharat

R Balasubramaniam

Ravi, a young worker in Coimbatore, six months into his first formal job at a small manufacturing unit, recently received credit of ₹7,500 in his bank account, separate from his monthly salary. The amount was disbursed automatically following completion of six months of continuous employment. His family had previously been engaged only in informal work, without contracts, provident fund contributions or any documented record of employment, and this was the first occasion on which his employment had been formally recorded and accompanied by a benefit of this kind.

The payment he received is his first installment under Part A of the Pradhan Mantri Viksit Bharat Rozgar Yojana (PM-VBRY), introduced in the Union Budget 2024-25 as part of the Prime Minister’s Package for Employment and Skilling. Under this provision, first-time employees joining EPFO-registered establishments with monthly earnings below ₹1 lakh receive a cash incentive of up to ₹15,000, disbursed in two installments, the first after six months of work and the second after twelve months. The payment is made via direct benefit transfer, linked to the worker’s Universal Account Number on the EPFO portal, and deposited into a savings instrument to build a financial cushion for the worker.

For Ravi, these six months were not merely a qualifying period. They were the months in which he gained familiarity with his workplace, acquired the basic skills of his trade and began to build an employment record where none had existed before.

BENEFITING SMALL BIZ

This period mattered for his employer too, a small manufacturing unit that had taken him on as part of its expansion. Part B of PM-VBRY provides that employers who create employment above their existing baseline receive a government contribution of up to ₹3,000 per additional employee per month, over two years across sectors and over four years in manufacturing. The contribution offsets part of the cost that a firm bears in the early months of a new hire, when onboarding and training are underway and a worker without prior formal experience is still becoming productive.

By easing this initial cost, the provision extends the scheme’s reach to small businesses of the kind that employed Ravi. For a country with India’s demographic profile, a young and growing workforce presents an opportunity to drive economic growth through employment-led development toward a Viksit Bharat by 2047. The extent to which new entrants enter formal employment, with access to social security and institutional protections, will influence how the benefits of growth are experienced across households and communities. PM-VBRY aims to strengthen the bridge from Swatantra Bharat to Samriddha Bharat and seeks to incentivise the creation of more than 3.5 crore formal jobs over two years.

Since becoming operational, 60 lakh first-time employees have joined the formal workforce through the scheme. Of these, 43.26 lakh, nearly 71 per cent, are in the 18 to 30 age group, and 18.04 lakh, close to 30 per cent, are women entering formal employment for the first time. These workers span expert services, engineering, trading, construction, education, healthcare, textiles and hospitality, reflecting uptake across a wide spread of formal establishments.

SOCIAL SECURITY

Beyond the incentive itself, what Ravi has gained is access to a broader net of social security — through provident fund contributions, insurance protections and statutory employment benefits. For many first-time formal workers like him, this represents an entry into social security coverage and a structured employment relationship. The six-month continuous employment condition is intended to ensure that jobs created under the scheme translate into genuine career foundations. Sustained formal employment builds transferable skills, instils professional norms and strengthens future employability, generating benefits that extend beyond the period of support provided under the scheme.

The creation of employment opportunities is an important policy objective. Equally important is ensuring that workers like Ravi are able to establish a sustained presence within the formal economy, where employment is accompanied by social security coverage and institutional protections.

As more workers complete six months, a year, and beyond in formal jobs, a larger share of the workforce enters the social security net, and small establishments build the habit of formal hiring. With more than 3.5 crore jobs projected under the scheme, this gradual widening of the formal economy represents a critical step toward building a workforce capable of powering India’s development journey.

In a first, US pips Qatar as India’s largest LNG supplier during March-May

Rishi Ranjan Kala New Delhi

The first 90 days of the West Asia conflict significantly altered India’s liquefied natural gas (LNG) imports trade, albeit in the short term, with the US emerging as the largest supplier for the first time, piping Qatar.

Data from Kpler show that during the March-May 2026 quarter, Washington supplied 1.5 million tonnes (mt) of LNG to India, compared to a mere 0.1 mt by Qatar. This is against Qatar supplying 3 mt during March-May 2025 against 0.5 mt by the US.

The global real time data and analytics provider pointed out that LNG imports weakened in March 2026 before recovering in April-May. Qatar’s share dropped sharply in recent months, while the US, Oman, Nigeria and Angola became more important sources of supply.

CUMULATIVE IMPORTS

India’s cumulative LNG imports for the first 90 days (March-May 2026) stood at 5.8 mt, a decline of 6.5 per cent on an annual basis.

In terms of import share, Washington surged to the top, accounting for more than one-fourth (25.86 per cent) of India’s cumulative LNG imports during March to May this year, compared to a little over 8 per cent in the year-ago period. On the other hand, Qatar’s share slipped from more than 48 per cent during March-May 2025 to just 1.72 per cent during March-May 2026.

The conflict also significantly impacted the share of top suppliers in West Asia (Qatar, the UAE, Saudi Arabia and Kuwait), which fell to 29.31 per cent in March-May 2026 from a whopping 74.2 per cent a year ago. Asian buyers were forced to secure higher-priced volumes to offset disrupted long-term LNG deliveries from Qatar and the UAE.

In March–April 2026, nearly 100 spot cargo tenders were issued in Asia, up from 89 in the same period in 2025, with India issuing tenders for 44 cargoes, double a year earlier, the Gas Exporting Countries Forum (GECF) said.

KEY SUPPLIER

Analysts and trade sources said that Washington emerged as the key balancing actor in the global LNG market after the West Asia conflict led to closure of the Strait of Hormuz (SoH), effectively choking half of India’s natural gas requirement.

As per Gastech, the world’s fourth-largest importer of LNG purchased 27 mt of LNG in FY25, of which 11.2 mt were sourced almost entirely from Ras Laffan. The attack on QatarEnergy’s Ras Laffan facility by Iran in April caused wide-scale damages and choked almost half of India’s LNG consumption. For comparison, about 93 per cent of Qatar’s and 96 per cent of the UAE’s LNG exports transited through the SoH, representing almost one-fifth of global LNG trade in 2025. There are no alternative routes to bring these volumes to market, said the International Energy Agency (IEA).

In 2025, Ras Laffan produced 112 billion cubic metres (bcm) of LNG, as well as 300,000 barrels per day of liquefied petroleum gas (LPG) and 180,000 barrels per day of condensate, the IEA said.

The GECF said that US LNG exports increased by 2.4 mt and 1.6 mt year-on-year in March and April 2026, respectively, supported by the ramp-up of production at recently commissioned LNG facilities. While Europe remained the largest destination, incremental volumes were increasingly redirected to Asia, reflecting tighter regional balances and stronger price signals in Asian spot markets. Destination flexibility of US LNG enables off-takers to redirect cargoes to markets offering the highest netback prices, enhancing short-term supply responsiveness, it added.

INDIA'S LNG IMPORTS (MARCH-MAY 2026 VS MARCH-MAY 2025)

Country	March-May 2026 (mt)	Import Share (%)	March-May 2025 (mt)	Import Share (%)
US	1.5	25.86	0.5	8.07
Oman	1.4	24.14	0.5	8.07
Nigeria	1.3	22.41	0.5	8.07
Angola	0.9	15.52	0.1	1.60
UAE	0.2	3.45	1.1	17.74
Qatar	0.1	1.72	3.0	48.39

Source: Kpler; MT: Million Tonnes; %: Percentage Share

Ageing population and rising debt could push TN towards a fiscal trap, warns White Paper

Sindhu Hariharan Chennai

Tamil Nadu’s fiscal position has deteriorated sharply since 2021, marked by rising debt, record revenue deficits, slowing growth in own-tax revenues and mounting committed expenditure, according to a White Paper on State finances released by the newly elected TVK government on Tuesday.

The report identifies plugging revenue leakages through better administration as a key priority even as the government seeks to restore fiscal health while honouring its welfare-oriented electoral commitments. Releasing the report, Finance Minister N Marie Wilson said the deterioration for fiscal correction was particularly urgent as Tamil Nadu is ageing faster than any other large State, leading to a shrinking tax base and rising social security and healthcare obligations.

6 KEY FINDINGS

Among its six principal findings, the report noted that Tamil Nadu’s total debt was projected to cross ₹10 lakh crore in FY26. Including off-Budget liabilities, contingent liabilities and guarantees, the State's total fiscal exposure had risen to ₹13.18 lakh crore.

The debt-GSDP ratio stood at 28.3 per cent, remaining consistently elevated and higher than that of peers. Furthermore, committed expenditure had risen from about 60 per cent of revenue receipts to 64 per cent, leaving limited fiscal space for capital expenditure.

REVENUE DEFICIT

The White Paper estimated the revenue deficit in FY26 at 2.22 per cent of the GSDP, the highest in six years and, in absolute terms, higher even than during the Covid-hit FY21. This deficit is estimated to be approximately 2.5 times that of Karnataka and Maharashtra.

According to the report, the widening revenue deficit since FY23 is attributable to the introduction of new recurring expenditure commitments without corresponding revenue mobilisation, the deferral of certain own-tax reforms, and other structural fiscal pressures.

PEER COMPARISON: OUTSTANDING DEBT AND LIABILITIES (AS % TO GSDP)

State	2021-22	2025-26 RE
Tamil Nadu	28.8	28.3
Karnataka	23.8	23.4
Maharashtra	19.8	19.7
Gujarat	19.3	17.6

Source: White Paper on the Fiscal Management of Tamil Nadu

Regulating the Digital Frontier: Evidence from Online Adult Content

 The regulatory context for online adult content is part of a broader global trend where governments are increasingly targeting digital platforms to restrict access to content, often motivated by concerns regarding addiction, misinformation, or harms to minors. This larger landscape of online activity regulation includes diverse efforts such as China’s broad censorship regime, targeted bans on specific platforms like TikTok in India or Twitter/X in Brazil, and social media restrictions for minors in Australia.

Within this broader environment, the regulation of online pornography in the United States has recently shifted toward state-level age verification mandates, which represent some of the most aggressive attempts to regulate online content in the country.

The U.S. Regulatory Framework

The current regulatory push began in earnest with Louisiana’s House Bill 142 on January 1, 2023, which established a template subsequently adopted by 24 additional states. Key features of this regulatory model include:

• Verification Requirements: "Commercial entities" that distribute material "harmful to minors" on websites where such content constitutes a "substantial proportion" must implement reasonable age verification methods. These methods typically involve uploading a government-issued ID, providing credit card information, or using biometric tools like facial recognition.
• Enforcement and Penalties: Enforcement primarily occurs through the court system, where state attorneys general or private individuals can sue non-compliant websites. Penalties for failure to comply are substantial, often reaching thousands of dollars per day of violation.
• Legal Precedent: While previous attempts to protect minors from online obscenity were struck down (e.g., Reno v. ACLU in 1997), the legal landscape shifted in June 2025 when the Supreme Court upheld Texas's age verification law in Free Speech Coalition, Inc. v. Paxton, affirming the government's interest in protecting minors.

Regulatory Challenges and "Leakage"

The sources highlight that regulating online activity presents unique challenges not found in offline markets, leading to various forms of "leakage" that can mute a policy's impact:

• Platform Non-compliance: Dominant sites like Pornhub have chosen to block access entirely in many states to lead legal battles and avoid public relations crises. Conversely, other major competitors like XVideos and XNXX, headquartered abroad, have continued to operate without verification requirements, relying on the practical difficulties of cross-border enforcement.
• Technological Circumvention: Digital consumers can often bypass state-level restrictions using Virtual Private Networks (VPNs) to mask their location. The sources find that roughly 30% of pre-restriction browsing time persisted through such circumvention.
• Alternative Paradigms: Due to these challenges, some proponents—including Pornhub’s parent company, Aylo—advocate for "device-based" age verification. In this model, smartphones or computers would collect and transmit verified age information directly to websites, potentially reducing VPN-based evasion, though this would not prevent users from substituting to non-compliant sites.

Ultimately, the effectiveness of these regulations depends heavily on the ease of technological circumvention and the availability of non-compliant substitutes, factors that policymakers must consider when designing digital regulations for any content category.

Platform responses to age verification laws vary significantly, often dictated by a site's market position, geographic location, and history of legal scrutiny. In the broader context of regulating online activity, these diverse responses create a fragmented landscape that significantly affects the efficacy of any given policy.

The sources identify three primary categories of platform response:

1. Total Access Blocking

The most prominent response was led by Pornhub, the world's most visited adult website, which chose to block access entirely for all users (both adults and minors) in most states that enacted these laws.

• Motivations: The sources suggest Pornhub chose this "aggressive" stance to lead the industry's legal battle against the mandates and to avoid high-profile public relations crises, especially given its history of scrutiny regarding content moderation.
• Legal Strategy: By blocking access, the company could more clearly challenge the laws' constitutionality without risking the massive daily fines (up to $5,000–$10,000 per violation) stipulated in state legislation.

2. Active Compliance

Other platforms chose to remain accessible by implementing the "reasonable age verification methods" required by the laws.

• Mechanism: These sites typically utilize third-party verification providers to handle government-issued IDs, credit card data, or biometric age estimation (such as facial recognition).
• Rationale: This approach allows sites to maintain their user base and revenue streams in regulated states while shifting some of the legal and data-privacy risks to specialized verification firms.

3. Strategic Noncompliance

The sources highlight that a major portion of the adult content market—notably XVideos and XNXX, the second and third most visited sites—chose not to implement any verification systems.

• The "Enforcement Gap": These sites often rely on the practical difficulty of cross-border enforcement. For instance, Pornhub’s parent company (Aylo) is based in Canada, while the parent company of XVideos and XNXX (WGCZ Holding) is based in the Czech Republic, creating jurisdictional hurdles for state attorneys general.
• Impact on Regulation: This noncompliance is a primary driver of "leakage." The study found that 49% of pre-law browsing time was spent on websites that never restricted access, meaning nearly half of the regulated activity continued completely unaffected by the new laws.

Implications for Online Regulation

These varied platform responses demonstrate the difficulty of regulating a global digital frontier with local laws. When a dominant, compliant platform like Pornhub exits a local market, users do not necessarily stop the behavior; instead, they often substitute toward noncompliant competitors (accounting for 10% of baseline consumption) or use VPNs to access the blocked sites (accounting for 31% of baseline consumption). Consequently, the effectiveness of digital regulation depends less on the law itself and more on the uniformity of platform compliance and the ease with which users can find substitutes.

In the broader context of regulating online activity, the sources highlight that digital consumers have a unique ability to adapt to restrictions, making the ultimate impact of such policies uncertain. When U.S. states implemented age verification laws for adult websites, user behavioral responses were characterized by four distinct channels: noncompliance, circumvention, substitution, and cessation.

According to the study, for every 100 hours of pornography consumed before the laws took effect, the breakdown of post-law behavior was as follows:

1. Noncompliance (50 Hours)

The largest share of consumption persisted simply because many websites did not implement the required restrictions. Approximately 49% of pre-law browsing time was spent on websites like XVideos and XNXX that chose not to comply with state mandates, allowing users to continue their habits without interruption.

2. VPN-Based Circumvention (30 Hours)

Users frequently bypassed geographic blocks by using Virtual Private Networks (VPNs) to mask their physical location.

• Persistent Access: Roughly 31% of baseline consumption persisted through this method.
• Young Adult Adoption: The sources find that young adults (aged 18–24) engaged in more VPN-based circumvention than older age groups, likely due to higher technological sophistication.

3. Platform Substitution (10 Hours)

When dominant sites like Pornhub blocked access, users often migrated to noncompliant competitors.

• Market Shift: Approximately 10% of baseline consumption was substituted from compliant sites to those that remained open.
• Concentrated Migration: Most of this traffic flowed to the remaining top-tier noncompliant sites rather than "fringe" adult websites.

4. Cessation (10 Hours)

A minority of users stopped visiting adult websites altogether in response to the regulations.

• Overall Impact: The sources estimate that total pornography consumption fell by approximately 10% (or roughly 0.5 minutes per week for the average user).
• Subgroup Differences: Cessation was notably higher in households with children when using desktop computers, which may suggest that the laws were more effective at reducing access for minors or that parents were more likely to stop using the sites on shared devices. Conversely, cessation was lower among young adults compared to those aged 25–44.

Implications for Digital Regulation

These behavioral responses demonstrate that "leakage"—the continuation of targeted activity through alternative means—significantly mutes the impact of online regulations. Across every subgroup studied, total consumption fell by 15% or less, indicating that while access restrictions did reduce overall activity, the majority of pre-existing behavior persisted through technological workarounds or shifting to alternative platforms. This suggests that the effectiveness of digital regulation depends heavily on the cost of circumvention and the availability of non-compliant substitutes.

In the larger context of regulating online activity, the methodology employed in the sources stands out by using high-frequency, individual-level panel data to overcome the limitations of previous studies that relied on aggregate traffic or search trends. This approach allows for a granular decomposition of user behavior—specifically noncompliance, circumvention, substitution, and cessation.

The research methodology can be broken down into three main components:

1. Data Source and Scope

The study utilizes data from Comscore, a media measurement firm, covering a rotating panel of approximately 550,000 U.S. internet users from January 2022 through December 2024.

• Individual-Level Tracking: The data tracks specific "machines" (desktop and mobile devices), recording the exact timestamp, duration, and number of pages for every website visit.
• Stable Geographic Assignment: Crucially, geographic location is assigned based on stable demographic information rather than contemporaneous IP addresses. This allows researchers to observe browsing activity even when a user is using a VPN, a capability missing from methodologies that rely on IP-based tracking like Google Trends.
• Comprehensive Categorization: Researchers tracked activity across more than 200,000 adult websites, manually coding the top 25 sites as "compliant" or "noncompliant" based on whether they implemented state-level restrictions.

2. Empirical Strategy: Stacked Difference-in-Differences

To identify the causal effect of regulation, the authors employ a stacked difference-in-differences (DiD) design.

• Exploiting Staggered Rollouts: The model takes advantage of the fact that age verification laws and subsequent website shutdowns (primarily Pornhub's) occurred at different times across 25 states.
• Event Study Framework: The analysis compares trends in pornography consumption in treated states to control states (those where shutdowns had not yet occurred or never occurred) during a window ranging from 16 weeks before to 8 weeks after a shutdown.
• Fixed Effects and Clustering: The researchers include machine-by-cohort and calendar-week-by-cohort fixed effects to control for individual habits and time-varying shocks. Standard errors are clustered at the state level to ensure statistical robustness.

3. Data Cleaning and Limitations

The methodology includes specific technical choices to ensure data quality and acknowledges inherent limitations:

• Winsorization: To prevent results from being skewed by extreme outliers (unusually long browsing sessions), all session durations were winsorized at the 95th percentile.
• The "Private Browsing" Gap: A noted limitation is that the data does not capture visits made in private browsing modes (e.g., Chrome’s Incognito Mode). However, the authors argue this does not bias their results because private browsing does not circumvent state-level IP blocks.
• Adult-Only Focus: Because the panel consists entirely of adults, the methodology measures how intended users (adults) respond to laws meant to protect minors.

Methodological Advantages over Prior Research

The sources emphasize that this methodology improves upon existing literature in several ways:

• Quantifying Minutes: Unlike Google Trends, which uses normalized search intensity, this study measures the exact number of minutes spent on platforms.
• Substitution Patterns: It can track substitution to the "full set" of alternative websites rather than just a few popular ones.
• Demographic Heterogeneity: The individual-level data allows researchers to see how responses differ by age, gender, and the presence of children in a household.

The sources perform a heterogeneity analysis to understand how different subgroups of users and device types respond to age verification mandates. This analysis is critical because it examines whether the regulations—intended to protect minors—actually affect users differently based on their age, technological literacy, or household environment.

Key findings from the heterogeneity analysis include:

Age and Technological Sophistication

The researchers focus on young adults (aged 18–24) as a proxy for how minors might respond, given that direct data on minors was unavailable.

• Lower Cessation: Young adults exhibited less cessation (stopping usage) compared to the 25–44 age group.
• Higher Circumvention: This group engaged in significantly more VPN-based circumvention, which the authors attribute to their likely higher level of technological sophistication.

Households with Children

To assess the impact on potential minor access, the study compared desktop machines in households with children to those without.

• Increased Effectiveness: Cessation was larger in households with children present than in those without.
• Interpretations: This could suggest the laws were more effective at reducing access for minors on shared family computers, or that parents in these households were more likely to cease usage altogether once the barriers were implemented.

Device Type and Usage Intensity

The analysis also looked at how the platform (mobile vs. desktop) and the user's baseline habits influenced their reaction:

• Mobile vs. Desktop: Mobile devices showed significantly higher baseline usage (18.8 minutes per week) compared to desktops (2.3 minutes per week). However, desktop users showed higher rates of cessation (approximately 13%) compared to mobile users (approximately 4%) [Figure 3, 95].
• Heavy vs. Moderate Users: Users categorized as "Heavy" Pornhub consumers showed greater cessation in percentage terms than "Moderate" users [Figure 3, 95].

Core Takeaway: The "Leakage" Consistency

Despite these variations, a primary takeaway from the heterogeneity analysis is the consistent attenuation of the law's impact across all groups.

• Universal Persistence: In every subgroup studied—including different genders, income levels, and household types—total pornography consumption fell by 15% or less.
• The Power of Substitutes: Regardless of the demographic, the availability of noncompliant sites and the ease of VPN circumvention provided enough "leakage" to ensure that the vast majority of pre-law browsing behavior persisted.

Ultimately, while certain groups (like young adults) are more adept at circumvention, the presence of close substitutes with low circumvention costs effectively muted the policy's impact across the entire user base.

The sources acknowledge several limitations inherent in their analysis of online adult content regulation, primarily stemming from data constraints and the scope of the study. These limitations are critical for understanding how the findings—such as the observed 10% reduction in total consumption—apply to the broader landscape of digital regulation.

Data Representation and Tracking Constraints

The study relies on a panel from Comscore, which presents specific challenges regarding how accurately it reflects the general population:

• Sample Selection: The Comscore panel is a selected sample of internet users and may not be perfectly representative of the U.S. population in terms of demographics and device-type usage.
• Awareness of Tracking: Because panelists are aware they are being tracked, their browsing behavior—specifically for sensitive content like pornography—might differ from that of the average unobserved user.
• Private Browsing Gap: The data does not capture visits made in private browsing modes (e.g., Google Chrome’s Incognito Mode). While the researchers argue this does not bias the results because private browsing cannot bypass geographic IP blocks, it does mean the study understates total consumption both before and after the laws took effect.

The "Minor" Data Gap

Perhaps the most significant limitation given the regulatory intent is the absence of direct data on minors.

• Primary Target Missing: The age verification laws were specifically designed to protect children under 18, yet the Comscore panel consists entirely of adults.
• Indirect Proxies: Researchers had to use young adults (18–24) and households with children as indirect proxies to infer how minors might react to the mandates. Consequently, the study's estimates reflect the impact on adult users rather than the primary population the laws aim to protect.

Geographic and Technical Measurement

The methodology for assigning users to specific states introduced potential for minor measurement errors:

• Market Mapping: Comscore Markets do not align perfectly with state lines. Researchers had to assign "machines" to states based on population majorities within overlapping markets, which could lead to errors in geographic assignment.
• VPN Identification: While the study can observe browsing activity even when a VPN is used (because geographic assignment is based on stable demographic data), it does not have a direct indicator for whether a VPN is active during a specific session. The persistence of activity on blocked sites like Pornhub is used as a proxy for circumvention.

Scope and External Validity

The sources also highlight limitations regarding the scope of their economic conclusions:

• Welfare Effects: The study documents a reduction in consumption but does not assess the welfare effects of these changes on either the consumers or society at large.
• Supply-Side Exclusion: The analysis focuses exclusively on the demand side (user behavior) and does not examine how these regulations affect the production of adult content or the performers involved.
• Generalizability: While the study identifies universal "leakage" channels like substitution and circumvention, the quantitative estimates are local to the adult website market and may vary in other regulated digital sectors like social media or online gambling.