RBI Bulletin - June 2026

 Monetary Policy Statement, 2026-27: Resolution of the Monetary Policy Committee (MPC) June 03 to 05, 2026

Monetary Policy Decisions The Monetary Policy Committee (MPC) held its 61st meeting from June 3 to 5, 2026, under the chairmanship of Shri Sanjay Malhotra, Governor, Reserve Bank of India. The MPC members Dr. Nagesh Kumar, Shri Saugata Bhattacharya, Prof. Ram Singh, Dr. Poonam Gupta and Shri Indranil Bhattacharyya attended the meeting.

After a detailed assessment of the evolving macroeconomic and financial developments and the outlook, the MPC voted unanimously to keep the policy repo rate under the liquidity adjustment facility (LAF) unchanged at 5.25 per cent. Consequently, the standing deposit facility (SDF) rate remains at 5.00 per cent and the marginal standing facility (MSF) rate and the Bank Rate remain at 5.50 per cent. The MPC also decided to continue with the neutral stance.

Growth and Inflation Outlook

Global Outlook As the West Asia conflict prolongs without any meaningful resolution in sight, risks to both inflation and growth have increased. Energy markets have been volatile; crude oil reserves are declining and global commodity prices have firmed up. Faced with difficult trade-offs, monetary policy has turned more cautious, and major advanced economy central banks are likely to pivot towards monetary policy tightening. Global financial markets have shown mixed trends, with equities remaining buoyant driven by AI optimism, while sovereign bond yields have hardened on fiscal sustainability concerns and inflation worries. The US dollar index has appreciated recently amid shifting rate expectations and changing risk sentiment.

Domestic Outlook As per several high frequency indicators, domestic economic activity remained largely steady since the outbreak of the conflict. Private consumption has been resilient, while fixed investment maintained its momentum despite cost pressures. Merchandise exports recorded strong growth in April 2026, though elevated freight and insurance costs remain a drag. Services exports continued to be robust. While the economy has withstood the conflict spillovers with limited impact so far, the strains are increasingly becoming visible.

Looking ahead, elevated energy and other commodity prices coupled with continued supply disruptions are likely to affect economic activity. While import diversification in affected commodities has helped in improving supply, it comes at a higher cost. The full impact will depend on the duration of the conflict, time taken for normalisation of supply chains, and the burden-sharing approach among stakeholders. The south-west monsoon is expected to be deficient, with implications for agricultural activity and rural demand; however, programmes for crop diversification and water conservation are expected to mitigate this impact.

Furthermore, sustained momentum in services, the continuing impact of GST rationalisation, and broadly stable employment conditions should support urban consumption. Strong capacity utilisation, sustained credit flows, and the government’s capex are expected to support investment activity. While weak global demand remains a headwind for merchandise exports, services exports are expected to remain steady. Several measures undertaken by the Government to ramp up domestic gas and crude supplies and support MSMEs have strengthened the economy’s resilience.

Taking all these factors into consideration, real GDP growth for 2026-27 is projected at 6.6 per cent, with Q1 at 6.6 per cent; Q2 at 6.3 per cent; Q3 at 6.5 per cent; and Q4 at 6.8 per cent.

Headline CPI inflation inched up to 3.4 per cent in March and 3.5 per cent in April 2026. Fuel inflation remained modest as retail prices were largely unchanged despite spikes in international energy prices. Core inflation remained at 3.7 per cent. Since May, however, retail fuel prices were raised by 7.4 per cent for petrol and 8.4 per cent for diesel, implying a direct impact of about 36 basis points on headline inflation.

Considering these factors, CPI inflation for 2026-27 is projected to be 5.1 per cent, with Q1 at 4.2 per cent; Q2 at 5.1 per cent; Q3 at 5.9 per cent; and Q4 at 5.4 per cent. Core inflation is projected at 4.7 per cent. These forecasts are subject to upside risks from global supply chain disruptions and monsoon uncertainty, though adequate foodgrain stocks provide some comfort.

Rationale for Monetary Policy Decisions The global environment has deteriorated since the last policy meeting. The adverse implications of supply chain disruptions and elevated energy prices are reflected in the moderation of growth and increased inflation projections. CPI inflation remains below the target despite the global shock, and underlying inflation pressures continue to be benign. However, generalisation of inflation through second-round effects on expectations and wages warrants a close vigil.

The MPC was of the opinion that there are considerable risks to the baseline assessment due to uncertainty about the duration of the conflict and the pace of restoration of supply chains. Additionally, the food outlook remains uncertain due to El Niño and sub-normal monsoon forecasts. Although risks of higher inflation have amplified, the MPC felt it would be prudent to wait for greater clarity. Accordingly, the MPC voted to keep the policy rate unchanged and will continue to remain data-dependent and closely monitor developments. The MPC also decided to retain the neutral stance.

The minutes of the MPC’s meeting will be published on June 19, 2026. The next meeting of the MPC is scheduled for August 3 to 5, 2026.

Resilience by Design: Lessons from India’s Banking Sector

Shri Swaminathan J.

Speech by Shri Swaminathan J, Deputy Governor, Reserve Bank of India, on June 1, 2026, at the School of International and Public Affairs (SIPA), Columbia University.

Distinguished faculty members, dear students, ladies and gentlemen. It is a pleasure to be here at Columbia University’s School of International and Public Affairs. SIPA was established in 1946, in the aftermath of the Second World War, to deepen understanding of global affairs and prepare professionals for public service across countries, institutions and disciplines.

We meet at a time when the global policy conversation is again crowded with large themes: geopolitics, climate change, artificial intelligence, technological disruption and the reordering of supply chains. Against that backdrop, banking resilience may seem like a quieter subject. But it has one distinct feature: when it is absent, its importance is immediately recognised. A weak banking system can quickly transmit stress from financial balance sheets to firms, households, public finances and the broader economy. I would like to approach it today through India’s experience.

India’s current position: strength with vigilance India today stands on a relatively strong macroeconomic footing. Even amid geopolitical uncertainty, supply-chain disruptions and volatile commodity conditions, domestic economic activity has shown resilience, supported by strength in industrial and services activity, broad-based demand and improving corporate performance. Inflation is within the tolerance band and external vulnerabilities remain manageable. The Indian financial system enters this uncertain phase with strength: healthier balance sheets, comfortable capital buffers, improved profitability and non-performing assets at multidecade lows.

This position of strength is encouraging. But the best time to build resilience is when conditions are favourable. Central banks are sometimes seen as cautious voices in otherwise optimistic times, expected to ask difficult questions just when the party appears to be going well. Risk has a habit of building quietly in good times and introducing itself loudly when conditions change. Buffers, governance and risk discipline must be strengthened when growth is strong, asset quality appears comfortable, and risk appetite naturally rises. Resilience must therefore be built before it is tested.

India’s recent banking resilience reflects policy learning, supervisory vigilance, stronger prudential frameworks, transparent recognition of stress, credible repair mechanisms and improvements within banks themselves. Banking resilience does not arise automatically from growth or favourable conditions. It has to be designed at multiple levels: in the rules that govern banks, in the supervisory systems that detect vulnerabilities, in the resolution architecture that addresses stress, and in the behaviour of banks themselves. Let me illustrate this through five recent dimensions of resilience by design: transparent recognition of stress, balance sheet strengthening, stronger supervision, calibrated and adaptive regulation, and resilience within banks themselves.

Recognition of stress The first dimension is transparent recognition of stress. Risk often builds when conditions appear favourable. During an upswing, collateral values look adequate, projected cash flows appear reasonable, and optimism becomes embedded in credit appraisal. India’s post-2015 asset quality experience brought this into focus. The stress reflected a combination of factors, including rapid credit growth in certain sectors, challenges with long-gestation projects, delays in stress recognition, and gaps in risk management.

The Asset Quality Review was more than an accounting exercise; it changed the information regime of the banking system. Recognition required banks to provision, owners to recapitalise, borrowers to negotiate, and supervisors to intervene. Transparency changes incentives. While recognition affects reported profitability and market perception, delayed recognition is usually more costly as it weakens credit discipline and increases the eventual burden of resolution.

Balance sheet strengthening Recognition must be followed by a credible chain of action leading to balance sheet strength. Recognition without resolution can leave banks constrained. In India, this phase involved coordinated action across the public policy ecosystem. The Government provided the legal, fiscal, and institutional architecture, including the Insolvency and Bankruptcy Code (IBC). Recapitalisation of public sector banks helped absorb losses and restore lending capacity, while consolidation sought to create institutions with greater scale and capital strength.

The banking system itself also undertook significant balance sheet strengthening. Banks improved provisioning, pursued recoveries and write-offs, raised capital and placed a sharper focus on asset quality. The movement towards more transparent, better-provisioned and diversified balance sheets has been a vital part of the resilience journey.

Stronger supervision and prudential discipline The Reserve Bank’s supervisory approach has evolved from point-in-time entity-level compliance to a more holistic, risk-based and forward-looking assessment. It covers governance, assurance functions, conduct, business models, technology risk, and cyber resilience.

A key element has been deeper engagement with Boards and senior management to identify the root causes of deficiencies, ensuring that issues are addressed at their source. The supervisory toolkit has been strengthened with off-site surveillance, stress testing, vulnerability assessments, and micro-data analytics. Modern supervision is not merely about checking compliance; it is about asking whether risks are understood and priced correctly and whether control functions have sufficient stature.

Calibrated and Adaptive Regulation Modern financial intermediation no longer fits neatly within traditional institutional boundaries. Credit, payments, and underwriting may involve banks, NBFCs, fintech entities, and third-party technology partners, making the system more interconnected. The regulatory response must be both entity-aware and activity-aware.

This approach is reflected in measures such as scale-based regulation for NBFCs and digital lending guidelines. During Covid-19, relief measures were designed to provide timely support while retaining a path back to normal prudential treatment through sunset clauses. RBI’s initiatives endeavour to protect customers without stifling innovation and to support inclusion while ensuring responsible conduct. Resilience by design means regulation by continuous review—rules must be stable but adaptive enough to remain relevant as markets evolve.

Resilience within banks Resilience has to be embedded inside banks. It must be visible in how banks originate assets, price risk, manage liabilities, and govern technology. A significant change in recent years has been the shift in portfolio behaviour away from large, lumpy corporate exposures toward more granular portfolios, including retail and MSME segments with clearer risk assessment.

This bank-level transformation matters because durability depends on internal behaviour. Resilience is built through everyday decisions: what is financed, how exceptions are approved, how early warnings are acted upon, and how accountability is enforced.

The next tests: complexity and uncertainty The next phase of banking resilience will be less about addressing known stress and more about managing complexity and uncertainty. Shocks can arise from varied sources: pandemics, geopolitical tensions, cyber incidents or sudden shifts in market sentiment. Banks must be made adaptable to risks whose timing and form are difficult to predict.

Technology can make banking faster, but it does not automatically make it wiser. AI, cyber risk, third-party dependencies, and climate-related risks will require ongoing attention from both banks and supervisors.

Conclusion Banking resilience is not a fixed achievement; it is a continuing institutional project. It is built through discipline across the balance sheet, transparent recognition of stress, calibrated regulation, and responsible conduct within banks. Strong banks require capital and technology, but they also require judgment, governance, accountability and institutions that learn. Resilience is not only about withstanding the last shock, but about building the capacity to respond well to the next one.

Thank you. Jai Hind.

State of the Economy

Introduction Geopolitical tensions and trade disruptions continue to test the global economy's resilience, with extended supply-side pressures leading to a sustained rise in commodity prices and inflationary expectations until early June. In its latest report, the World Bank downgraded global GDP growth projections while raising its inflation projections due to the West Asia conflict. However, the signing of an interim peace deal between the US and Iran in late June has provided a vital opening for normalisation.

The Indian economy has shown notable strength, with GDP growth in Q4:2025-26 reaching 7.8 per cent, driven primarily by private consumption and fixed investment. High-frequency indicators suggest this momentum has sustained into May 2026, supported by resilient domestic demand and strengthening industrial growth in the manufacturing sector. Headline CPI inflation in May 2026 increased to 3.9 per cent from 3.5 per cent in the previous month, reflecting broad-based increases across food, fuel, and core components. In its June 2026 review, the Monetary Policy Committee (MPC) unanimously decided to keep the policy repo rate unchanged at 5.25 per cent while maintaining a "neutral" stance as it awaits further clarity on global conflicts and monsoon risks.

Global Section The World Bank projects a slowdown in global growth for 2026, with a recovery expected in 2027. While risks remain skewed to the downside, the wider adoption of Artificial Intelligence (AI) and productivity reforms may support medium-term growth. Global Purchasing Managers’ Index (PMI) data showed widespread moderation in May, though the manufacturing sector outperformed services for the third consecutive month.

Commodity prices witnessed some softening in May as Brent crude oil prices declined from April's elevated levels, eventually correcting to below US$ 80 following the West Asia peace deal announcement. Headline inflation generally edged up across major advanced economies (AEs) and emerging market and developing economies (EMDEs) in May. Central banks have adopted cautious stances; while the Euro area and Japan pivoted toward rate hikes, the US and UK held rates unchanged.

Domestic Developments India's annual real GDP growth accelerated to 7.7 per cent for 2025-26, up from 7.1 per cent the previous year.

• Aggregate Demand: Robust private consumption and double-digit expansion in fixed investment supported growth. High-frequency indicators for May show continued resilience, with double-digit growth in E-way bills and electricity demand, the latter driven by a severe heatwave. Urban demand remained strong, reflected in accelerated passenger vehicle sales and domestic air passenger traffic. Conversely, rural demand showed some moderation in retail automobile sales.
• Government Finances: The Central Government’s gross fiscal deficit (GFD) for 2025-26 stood at 4.4 per cent of GDP, lower than both the previous year and revised estimates. State governments, however, experienced some slippages, with a consolidated GFD-to-GSDP ratio of 3.3 per cent.
• Trade and Supply: The merchandise trade deficit widened year-on-year in May 2026 due to higher crude oil prices, even as exports reached their highest level in recent years at US$ 45.2 billion. On the supply side, real gross value added (GVA) grew by 7.9 per cent in 2025-26, with industry and services both growing at 9.0 per cent. Foodgrains production reached a record 376.6 million tonnes, though the south-west monsoon is forecast to be below normal at 90 per cent of the long period average.

Inflation CPI headline inflation inched up to 3.9 per cent in May 2026, driven by broad-based increases. Food inflation saw a sequential pick-up across most sub-classes, and fuel inflation rose due to adjustments in retail prices for petrol, diesel, and CNG. Despite these increases, Indian households continue to pay some of the lowest cooking gas prices globally due to government and OMC absorption of costs. Wholesale Price Index (WPI) inflation rose to 9.7 per cent in May, its highest level in the new base series since April 2024.

Financial Conditions Surplus liquidity in the banking system moderated in May and June due to increased currency in circulation and higher government cash balances. G-sec yields softened following measures by the Reserve Bank and Government to attract foreign capital, including tax exemptions for foreign portfolio investors (FPIs). Bank credit continued to record double-digit growth (17.7 per cent y-o-y as of May 31), outpacing deposit growth.

On the external front, net FDI remained strong in April 2026 at US$ 6.6 billion, significantly higher than the US$ 1.6 billion recorded a year ago. While FPIs initially recorded net outflows, flows turned positive in mid-June following supportive policy measures. India’s foreign exchange reserves remain comfortable at US$ 682.3 billion, providing cover for over 10 months of imports.

Conclusion The global economic outlook remains fragile, and any breakdown in the recent US-Iran peace agreement could reignite risks to inflation, investment, and food security. India enters this period of turbulence with strong fundamentals, including high growth, anchored inflation expectations, and substantial foreign exchange buffers. However, the domestic outlook remains subject to risks from an adverse south-west monsoon.

Sluggish Expectations and the Policy View of Inflation

 Based on the source provided, the following is the full text of the article "Sluggish Expectations" by John H. Cochrane.

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Sluggish expectations

JOHN H. COCHRANE JUN 30, 2026

As part of a big revision of “Inflation”, a short book resulting from last year’s Brunner lecture, I wrote the following short section. I try to capture how central bankers talk about interest rates and inflation in a few simple equations. Previously, I discussed the venerable adaptive expectations model. There, expected inflation in the model is just last period’s inflation. That makes an interest rate peg unstable, and higher interest rates lower inflation going forward. I also discussed rational expectations. There expected inflation in the model is the expected inflation of the model, and forward looking. That makes an interest rate peg stable, but leaves multiple equilibria. Fiscal theory fixes those. It also means that higher interest rates eventually raise inflation, though it can go the other way in the short run.

It’s not really fair to say that central banks are stuck in adaptive expectations. They have heard about expectations since 1980, and they do think about expectations. They don’t, however, think that expectations react quickly to news, even though expected inflation in the model does react quickly to news. They then preserve the traditional property of the model, that higher interest rates lower inflation going forward, and avoid rational expectations indeterminacies.

Here is my effort to describe how central bankers view the world. This is section 4.10 of the new draft, and an invitation to send me comments about anything in the draft. Usually my job here is to write words about equations. Today the point is to write some simple equations about words.

Today’s policy world has a more nuanced view than the 1970s adaptive expectations I described above. A distillation of the current policy view might be called “sluggish expectations.”

This view acknowledges that expectations are important, but does not tie them rigidly to past experience (adaptive) or to the model’s predictions of the future (rational). In this philosophy, expectations vary through time and in response to various forces, many external to central bank actions. Expectations eventually respond to experience of inflation, though not in a predictable way. Faith that the central bank will eventually do something can “anchor” expectations through a period of inflation. But that faith and “anchoring” can evaporate, at which point a spiral breaks out. Expectations can also move in response to news about the future such as fiscal matters and other shocks, thus accommodating some of the many historical episodes adduced by forward-looking rational expectations. But this happens rarely, and usually only in large tumultuous episodes.

Central banks also measure expectations in surveys and bond markets. They treat these measures as somewhat exogenous disturbances that they should react to, as well as measures of people’s faith in central banks’ future actions that central banks should try to control by actions and statements.

Most of all, expectations do not react quickly to interest rates, even when the model predicts that actual inflation will react to interest rates. The expectations of the model are still different from the expectations in the model. Economists armed with the model could make a lot of money. That sluggish property preserves most of the traditional doctrines I captured above with adaptive expectations, but with nuance.

(Doctrines: Under adaptive expectations 1) Inflation is unstable under an interest rate peg. 2) Higher interest rates lower inflation, going forward. 3) By following the Taylor rule, central banks stabilize an economy which is naturally unstable. Under rational expectations 1) Inflation is stable under an interest rate peg. 2) Higher interest rates, on their own, raise expected inflation going forward. 3) Inflation is neutral in the long run. 4) Inflation is indeterminate under an interest rate peg. 5) By following a Taylor rule, central banks destabilize the economy and select a single equilibrium.)

To describe this view, I write out a little model:

$$x_t = -\sigma(i_t - \pi^e_t) + u_{x,t}$$ $$\pi_t = \pi^e_t + \kappa x_t + u_{\pi,t}.$$ $$\pi_t = (1 + \sigma\kappa)\pi^e_t - \sigma\kappa i_t + (u_{\pi,t} + \kappa u_{x,t}).$$

Here $x$ is output, $i$ is the nominal interest rate, $\pi$ is inflation, $\pi^e$ is expected inflation, $\sigma$ and $\kappa$ are parameters, and the $u$ are disturbances. The first equation is the “IS” equation. It says that higher real interest rates depress output. The second equation is the Phillips curve. It says that higher expected inflation or higher output push inflation up. Those are core central bank beliefs.

Eliminating output $x_t$, inflation is related to interest rates by [the third equation above]. The IS curve gives output directly. I add “demand” and “supply” disturbances, which move inflation and output around and to which the central bank responds. (With adaptive expectations $\pi^e_t = \pi_{t-1}$ and this is an unstable equation. With rational expectations $\pi^e_t = E_t \pi_{t+1}$ it’s stable. That’s the basis for the above doctrines.) The same equation holds at time $t+1$, and you can verify that the expectations in the model are not the expectations of the model.

Higher inflation expectations $\pi^e_t$ raise inflation and output right away. So worrying about survey and market expectations is important. But, to our central doctrines, there is no unstable spiral under an interest rate peg so long as expectations do not move, so long as they stay “anchored.” Inflation and deflation starts to spiral when current inflation or deflation starts to feed in to expected inflation. Then an initially slow inflation or deflation can suddenly pick up speed.

That’s why central banks “look through” inflation surges, so long as they believe expectations remain “anchored.” A spurt of inflation coming from shocks to the disturbances $u$ will go away on its own. That inflation may lead to a permanently higher price level, but central banks, having interpreted their mandate as a forward-looking inflation target with bygones bygone, do not care about that.

In 2021, for example, the Fed saw inflation surge. But as its forecasts, survey forecasts, and bond market expectations projected a return to 2% inflation, the Fed saw no urgency to move. The Fed only moved when it saw measures of inflation expectations start to creep up. It then interpreted the swift decline of inflation not as a real interest rate effect—since real interest rates were still sharply negative, and no recession followed—but as a sign that expectations had been re-anchored by the mere threat of action. Similarly, in discussing how to adapt to tariffs, a “temporary” inflation shock and a one-time price level increase, Waller (2025) argued that the Fed should again “look through” the shock and not respond.

This view also lacks an economic nominal anchor—nothing like the $M$ in $MV=PY$ or $B/P = EPV(s)$ to tie down the price level. The closest it comes is to view anchored expectations as the anchor for actual inflation, with no anchor for the price level. And at best that anchor comes from faith that the Fed would if necessary repeat 1980 in the event that inflation got out of control. Yet the Fed is curiously silent about such energetic measures. Are we at anchor or just floating in a calm sea?

Central banks can always raise interest rates, but they cannot lower rates much below zero. Thus, central banks have greater fear of downward de-anchoring and deflation spirals. Central banks were much more worried about the small deflation in 2008 in the zero bound era than they were about an upward inflation spiral in 2021. (They may also view the costs of deflation as larger than those of inflation.) Likewise, many analysts could attribute the swift inflation decline in 2022 while interest rates stayed well below inflation as a case of re-anchoring expectations, showing what the Fed might do in the future, while worrying earlier that deflationary expectations could become de-anchored and the Fed powerless.

In sum, the contemporary policy view still predicts that inflation and deflation spirals can break out. The absence of a spiral in the zero bound era remains a puzzle. “Expectations did not move” is a little easier epicycle to explain the lack of a spiral, but that ignores the constant contrary worry at the time.

So long as expectations are sluggish, higher nominal interest rates lower inflation. See the coefficient $-\sigma\kappa$ in the last equation. Writing it as

$$\pi_t = \pi^e_t - \sigma\kappa(i_t - \pi^e_t),$$

you can see that if expectations rose one-for-one with the nominal interest rate, inflation would rise and output would not move. That non-reactive quality, rather than the rigid adaptive scheme, is crucial to the Fed’s ability to lower inflation with higher interest rates.

However, higher interest rates only move inflation immediately in this little model. As long as inflation does not feed in to expectations, today’s interest rate only affects today’s inflation. There are, so far, no “long and variable lags.” In the adaptive expectations model a small initial inflation gets an expectational snowball going to create more future inflation.

I think the current policy view squares that circle in three ways. First, one can sprinkle lags into these equations to produce some dynamics. For example, people reason that higher interest rates take time to lower demand, via some unspecified friction. Second, lowering future inflation with sluggish expectations requires persistently high interest rates. High interest rates today lower today’s inflation, then high interest rates in the future lower future inflation. This may be a reason that central banks tighten and loosen in long waves. Third and most of all, the time and contingency it takes for inflation to feed in to expectations explains why the lags are both long and variable. A one-period adaptive expectations model produces too fast and too reliable a mechanism. Here, after a period of persistently high interest rates, resulting in a period of persistently low inflation, inflation breaks through people’s attention span. Only then, which may be a year or more later, do people wake up, change expectations, and monetary policy really has its effect.

In this view, expectations are also amenable to suasion by central banker speeches, policy frameworks, and “forward guidance.” If central bankers can talk down expectations, that improves the inflation-output tradeoff of the Phillips curve. The central bank can then lower nominal rates and enjoy lower inflation with no output cost. At the zero bound, central banks try to talk up expectations, such as by announcing a higher target or forward guidance. Indeed, since the Phillips curve in the 2010s seemed flat, with $\kappa$ near 0, much of the central bank view focuses on expectations alone as the determinant of inflation. Most of the art of central banking amounts now to expectations management. (Or at least it did through the end of the Powell era. Kevin Warsh has written about scaling back such efforts.) Alas, speaking loudly without a stick has often failed in the past to contain or boost inflation. Eventually if inflation does not do what central bankers want, they need something more than additional speeches.

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Note: Repetitive Substack subscription text and headers appearing in the original source have been removed for clarity.

Iran Update Special Report, July 1, 2026

 Iran Update Special Report, July 1, 2026 Data Cutoff: 2:00 PM ET Authors: Katherine Wells, Ben Rezaei, Parker Hempel, Nidal Morrison, Carolyn Moorman, and Nicholas Carl.

Key Takeaways

1. Iran is pressuring the United States to unfreeze significant financial assets and acknowledge Iranian sovereignty over the Strait of Hormuz as part of a memorandum of understanding (MoU). These concessions would strengthen Iran’s strategic position and potentially fund military reconstitution.
2. Iranian Parliament Speaker Mohammad Bagher Ghalibaf is attempting to build domestic support for the MoU through a June 30 interview, responding to backlash from anti-negotiation hardliners.
3. Ghalibaf suggested that Iran will continue to collect transit fees from vessels in the Strait of Hormuz, using this as evidence that the MoU recognizes Iranian sovereignty over the waterway.
4. Iranian officials are openly discussing expanding missile ranges beyond the current 2,000-kilometer limit. A senior adviser to the former Supreme Leader stated that "phased" guidance had been issued to increase both range and accuracy.

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Toplines

Iran’s Negotiating Position and Financial Demands Iran is using talks in Doha to push for the release of $6 billion in frozen assets and US recognition of its control over the Strait of Hormuz. These discussions, held on July 1 with Qatari officials, followed meetings between Qatar and US representatives Steve Witkoff and Jared Kushner. Iranian Deputy Foreign Minister Kazem Gharibabadi confirmed the talks aimed to accelerate a ceasefire in Lebanon, lift the US blockade on Iran, and release frozen funds. While Gharibabadi claimed an agreement was reached to use the $6 billion for "needed goods," US officials have denied agreeing to unfreeze the funds.

Strait of Hormuz Tolls and Sovereignty A major point of contention involves Iranian demands for transit tolls in the Strait of Hormuz. US officials reportedly warned Iranian negotiators that these demands could disrupt the entire MoU, arguing that a diplomatic agreement would provide more financial benefit than tolls. However, Ghalibaf has maintained that Iran will continue to collect fees, viewing it as a matter of sovereignty.

Internal Regime Dynamics The Pezeshkian administration is working to present a unified front. President Pezeshkian emphasized alignment with Supreme Leader Mojtaba Khamenei and the IRGC. To appease hardliners, the names of 11 Supreme National Security Council members who voted for the MoU—including ultra-hardliner Saeed Jalili—were made public. Despite these efforts, some regime elements remain concerned about violating "red lines," with 60 members of the Assembly of Experts issuing a formal warning to negotiators.

Missile Program Expansion Iran appears to be moving toward developing intercontinental ballistic missile (ICBM) capabilities. Following a failed March 2026 attempt to strike the US base in Diego Garcia (approximately 3,700 km away), 85 parliamentarians signed a letter supporting the development of missiles capable of reaching the United States. Current long-range Iranian missiles, such as the Emad and Sejjil, are capped at 2,000 kilometers.

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US-Iran Negotiations

(See Topline section).

Maritime Activity in the Strait of Hormuz and Persian Gulf

Nothing significant to report.

US and Israeli Air Campaign

Nothing significant to report.

Iranian Domestic Affairs

(See Topline section).

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Iran’s Axis of Resistance

Lebanese Hezbollah and the Israeli Campaign in Lebanon The IDF has postponed its withdrawal from "pilot zones" in southern Lebanon, including areas around Zawtar el Gharbiyeh and Nabatieh. Withdrawal is contingent upon the establishment of a Military Coordination Group for Lebanon (MCG4L) and efforts by the Lebanese Armed Forces (LAF) to disarm Hezbollah in these zones. This "clear-hold-build" strategy is part of the Trilateral Framework Agreement’s Security Annex. The US will vet LAF soldiers involved in the coordination group to prevent Hezbollah from accessing sensitive information.

Other Axis of Resistance Activity In Iraq, leaders of the Shia Coordination Framework have refused Prime Minister Ali al-Zaydi’s request to arrest senior Iranian-backed militia leaders as part of an anti-corruption drive, fearing "security tensions". Despite this, reports indicate that Hussein Moanes, a political leader for Kataib Hezbollah, has fled the country. Zaydi’s campaign follows US pressure to dismantle militia-linked financial networks.

Newspaper Summary - 020726

 The following is the article titled “Govt asks Meta to pause WhatsApp user names rollout over fraud risks,” as it appeared in the sources:

Govt asks Meta to pause WhatsApp user names rollout over fraud risks

EXPLANATION SOUGHT. Notice seeks reply within three days; Meta says safeguards in place to prevent misuse

S Ronendra Singh New Delhi

Following the recent introduction of WhatsApp’s ‘user names’ feature, the Centre has issued a formal notice to Meta, seeking a detailed explanation of the new function’s functionality within three days.

“The government has directed Meta not to roll out the ‘user names’ feature until consultation on the matter is over,” highly placed government sources said. The government believes the feature can be misused in a manner similar to Telegram, which was temporarily blocked during NEET-UG 2026 over concerns that anonymous accounts were being used to circulate leaked examination material.

DANGEROUS MOVE “This is not acceptable... We will ask rules, and low and if required, law will be made to stop WhatsApp from user-names... logic is it is dangerous, not good for society, not for anyone. It is prone to impersonation... Anyone can open an account in another name, and people may do financial frauds using fake names,” a senior government official said.

In its formal communication to Meta, the Ministry of Electronics and Information Technology (MeitY) said it had taken note of WhatsApp’s public announcement that it had commenced a phased global rollout of the feature, including in India. According to the notice, the feature would allow users to reserve unique user names and, once fully activated, “initiate and conduct conversations by exchanging user names alone, without disclosing their mobile telephone numbers”.

FRAUD PRONE The Ministry said it was concerned that if this feature is ‘enabled’, the ‘recipient’s’ mobile number will no longer be visible to a first-time contact” and that the change “may materially increase the incidence of online fraud, phishing, digital arrest scams and impersonation attacks, by enabling bad actors to solicit and message victims”.

Accordingly, the Ministry directed Meta to explain “why regulatory action should not be initiated under the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, for failing to implement ‘due diligence’ obligations that may increase cybercrimes”. It reminded the company that WhatsApp, as a “significant social media intermediary”, is required to comply with due diligence obligations under the IT Rules.

The notice specifically referred to Section 79 of the IT Act governing intermediary liability protections; Rules 3 and 4 of the IT Rules relating to due diligence and identification of the first originator of information; and Sections 66C and 66D of the IT Act dealing with identity theft and cheating by personation using computer resources.

META CLARIFIES Responding to the government’s concerns, Meta said the feature had not yet been activated and will be introduced gradually later this year.

“We’ve announced the option for people to reserve their unique user name on WhatsApp. The ability to use a user name is not yet live and will be rolling out later this year,” a WhatsApp spokesperson said. Meta also stressed that users would still need a phone number to create and use a WhatsApp account.

According to the company, there will be multiple layers of protection against scams, including requiring users to know the user name before they can initiate a chat. It also said it has built-in systems that use AI and machine learning to proactively detect and remove impersonation accounts.

The following is the article titled “Rupee closes at three-week low of 95.24/dollar” as it appeared in the sources:

Rupee closes at three-week low of 95.24/dollar

Our Bureau Mumbai

The rupee posted its steepest single-day decline in over three weeks on Wednesday, weakening 58 paise to close at 95.24 against the US dollar, as aggressive dollar buying by importers, stop-loss triggers and a sharp rise in Brent crude oil prices overshadowed support from domestic equities and likely intervention-related dollar sales by state-owned banks.

The domestic currency ended at a three-week low. It had last touched this level since June 8, when it had lost 77 paise in a single session.

The rupee has now extended its losing streak for the fourth day, losing about 108 paise per dollar since June 18.

Wednesday's decline also follows a dismal May trade performance for the country, which showed a widening trade deficit as exports slowed and imports grew.

The following is the article titled “It’s finally pouring for RAINMUMBAI” as it appears in the sources:

It’s finally pouring for RAINMUMBAI

Daily trading in NCDE’s weather derivative hits ₹20 crore as the monsoon picks up

Vishwanath Kulkarni Bengaluru

Every cloud has a silver lining. The delay in the monsoon’s arrival in Mumbai may have dampened the initial enthusiasm for India’s first tradeable weather derivative, but the sudden downpour has now driving renewed interest in the contract called RAINMUMBAI. It is now seeing trade of ₹20 crore a day.

The National Commodity and Derivatives Exchange (NCDEX), India’s first exchange to launch rainfall futures last month, which has already seen trading of over 10,000 lots since the change officials expect the trade to pick up further as the South West monsoon progresses and retail and institutional interest builds.

“The initial response was not as per our expectation because there were no rains, but now it should pick up since the rains have come. It is an exact match with what is happening now,” said Arun Raste, CEO, NCDEX.

DRIZZLE TO DIVIDENDS

RAINMUMBAI, a rainfall index based on Mumbai’s monsoon precipitation, has seen its price and trading changing weather expectations. With trading activity expected to increase, prices softened as traders anticipated below-normal rainfall. With the monsoon now establishing over the city, the sentiment is reversing.

With trading activity steady state, the contract is already recording a turnover of ₹20 crore on a daily basis and RAINMUMBAI has an open interest of about ₹600 crore.

The turnover, Raste said, should improve going forward as rains continue and more investors become familiar with the product. Presently, institutional participants, including farmer producer organisations (FPOs) and a few weather derivative contract, are participating. The NCDEX is looking to introduce two more weather derivative products—one for the North-East Monsoon and another for the summer heat—some time later this year.

HEDGING HEAVENS

Weather, which impacts traditional commodity futures, is now a commodity itself as derived from the India Meteorological Department (IMD) data on the future price of a physical commodity.

As rainfall expectations evolve through the season, the contract’s price adjusts accordingly, allowing businesses exposed to weather risk such as agriculture, logistics, construction and power, as well as investors, to hedge their risks or take directional views on the progress of the monsoon.

The following is the editorial titled “Chipping away” from the July 2, 2026 edition of The Hindu BusinessLine:

Chipping away

Semiconductor push should be followed through

The Centre’s decision to approve a Budget proposal of around ₹1.25 lakh crore for the India Semiconductor Mission (ISM) 2.0 is a strong signal that India’s semiconductor ambitions remain a strategic priority. The allocation, substantially higher than the ₹76,000 crore earmarked for the first phase, comes at a time when the global race for chip supremacy is intensifying amid geopolitical tensions, supply chain disruptions and the growing centrality of semiconductors to economic and national security.

Over the past three years, India has moved from a passive consumer of chips to a credible destination for semiconductor investment. Twelve projects spanning fabrication, assembly, testing and packaging have been approved, attracting investments exceeding ₹1.5 lakh crore. The Tata Group’s fabrication project with Taiwan’s PSMC, Micron’s packaging facility and multiple OSAT projects are tangible evidence of this progress, placing India as more than just a back-office for chip design. Simultaneously, the Design Linked Incentive (DLI) scheme is nurturing a pipeline of indigenous fabless start-ups that could become tomorrow’s semiconductor champions.

However, semiconductor manufacturing requires enormous capital, long gestation periods and continuous technological upgrades. ISM 2.0 must therefore go beyond approving fresh projects. Existing facilities must be supported through expansion that enables them to scale up production. While India does not have sub-7nm leading-edge manufacturing capacity, or access to highly restricted EUV lithography machines, the domestic fabrication plan is anchored around 28nm, which is the workhorse for global electronics. This can cater to the demand for microcontrollers, EV powertrains, 5G modems, IoT sensors, and display drivers. This segment accounts for a significant share of global semiconductor demand and offers India a realistic entry point into the value chain. Strengthening ecosystem support, chip design capabilities and talent must continue.

Government procurement can play a catalytic role by mandating the use of domestically manufactured chips in public infrastructure, defence systems, railways, and BharatNet’s 5G rollout. Strategic Partnerships such as Tata Electronics’ supply agreement with Intel are encouraging, but the entire value chain must be incentivised for building a sustainable ecosystem. Beyond fabrication, chipmaking depends on access to critical minerals, advanced manufacturing equipment, and specialised talent. China’s control over exports of key minerals has underscored the vulnerabilities in global supply chains. India’s partnerships through initiatives such as the proposed Pax Silica alliance, therefore, acquire strategic significance. NITI Aayog’s estimates suggest an investment requirement of $135-180 billion over the next decade to build a globally competitive semiconductor industry. The Centre cannot shoulder this burden alone. Yet, sustained public funding can de-risk private investment and inspire long-term confidence.

The following is the article titled “6 lakh retail investors, LIC, MIT hit as KPIT dives 17% on revenue warning,” as it appeared on page 7 of the source:

6 lakh retail investors, LIC, MIT hit as KPIT dives 17% on revenue warning

THUMBS DOWN. Analysts downgrade the stock as tech major expects Q1 dollar revenues to decline 1%-2% y-o-y

Anupama Ghosh Mumbai

Shares of KPIT Technologies lost nearly 17 per cent on Wednesday to close at ₹587.55, almost a four-year low, wiping out significant market value for its shareholders, including 6 lakh retail investors, LIC and the Massachusetts Institute of Technology, as the Pune-based automotive software company issued a surprise profit warning on Tuesday.

AUTO MAJORS TO CUT

Analysts believe that while KPIT Technologies on Tuesday said it expects Q1-FY27 USD revenues to decline approximately 1 per cent year-on-year compared to Q1-FY26. The company attributed the shortfall to abrupt spending cuts by certain European automotive OEMs, triggered by profit warnings and adverse business conditions at those clients. Furthermore, it acknowledged the impact was not anticipated and came to light only in recent weeks.

According to Morgan Stanley, with a weak start to Q1-FY27, KPIT’s 18-22 per cent growth guidance for FY27 will be a tall task. Until Q4-FY27, it would be needed to grow its quarterly revenues by 5-8 per cent and margins by 20-30 bps every quarter. It has cut its price target on KPIT to ₹740 from ₹1,030.

Beyond revenue, KPIT warned that EBITDA margins for the June quarter will decline sequentially in Q1-FY27 — and at a sharper rate than revenues — as the company is limited in its scope for cost optimisation in such a short time frame.

KEY SHAREHOLDERS

KPIT is significantly owned by the public. While promoters hold 39.42 per cent, the public hold 59.81 per cent shareholding in the company. Among the public, mutual funds hold 12.09 per cent, and insurance companies hold 11.13 per cent. Retail investors hold 15.79 per cent.

JM Financial downgraded the stock to “Reduce” with a target of ₹620, cutting FY25-27 earnings estimates by 12-13 per cent and trimming the target PE to 35x from 45x. SBI Securities flagged the development as a near-term negative for KPIT and peers including LTTS and Tata Elxsi.

Kotak Securities said cyclical challenges will right-size expectations rather than change aspirations rather than being a structural issue. It has cut its rating from “Add” to “Reduce” (TAM). “This follows the significant increase in stock price in the last year. This has pushed valuation multiple in near-term. It has however downgraded KPIT to “Add” from “Long” with a target of ₹720,” it said.

KPIT CLARIFIES

Meanwhile, KPIT clarified that the expected impact as stated on Q1-FY27 revenues is based on "meaningful interactions" with multiple client actions. “We have also indicated the growth trajectory for the rest of the years will continue to see growth. Therefore, we expect FY27 revenue to be on similar range as Q1-FY27 revenue,” it said.

The following is the article titled “10 steps to reducing home prices” by Gurbachan Singh, as it appeared in the sources:

10 steps to reducing home prices

HOMING-IN. Amending the Land Acquisition Act and allowing for a higher floor space index in some areas are among the required measures

Gurbachan Singh

Houses, as they are, all said and done, are very high in urban India. The root of the problem lies in the public policy. This article presents a ten-point policy solution. It is a very long story but told briefly here. Some of it is an ‘out of the box’ story; but most of it is not.

First, the existing major cities are too big for further expansion at reasonable costs. We need new cities that are not extensions of existing small cities. But the public authorities are too small for this. We need public policy that enables the private sector to lead in new city development. The expansion needs to be holistic so that people actually shift in a phased manner. Home prices will be significantly lower and attractive in the new urban areas.

Second, in the existing big cities there is a regulatory mess. There are severe restrictions on real estate development, including FSI. There is a case for much higher floor space index in some areas, and better public utility and civic institutions like the Delhi Development Authority. The supply of homes will expand.

URBAN LAND PRICE

Third, with the massive expansion of supply of land for housing and price to above, the price of land can, in fact, rise in the short run. However, the long-run story is very different. As the number of houses in a city increases, and particularly after a while, their inflation-adjusted prices will fall. Accordingly, the price of land will fall. After some time, the house prices of homes will fall. We have international experience of such a causality here after a while — from house prices to urban land prices. This is the price of rural land at the boundaries of cities.

Fourth, there is a need to amend the Land Acquisition Act, 2013, which can contribute to reducing the price of rural land. The displaced farmers can be part owners of the new real estate on their existing small cities. This is not just for efficiency but for equity. It is a win-win for livelihood.

Fifth, with the policies suggested here, real estate prices will start coming down. This itself can reduce the incentives for the big investor demand. This can, in turn, increase the effective supply of real estate for end-users. We also have “retail” investor demand for homes. This is somewhat related to the low post-tax and inflation-adjusted returns on bank deposits, etc., due to financial repression, public sector banks, and tax laws. A change in policy will help here. This can tilt the “retail” investor demand from real estate to financial assets. This too will increase the effective supply of real estate.

Sixth, a part of the investor demand is due to the need to absorb black money. This is often justified with the argument that the black money may otherwise get invested in gold or in assets abroad through the hawala route. This is a case of capital outflow from the country, which needs to be discouraged. But the question is not about absorption of black money within the economy. Instead, we need to phase out the very generation of black money; this can, among other things, reduce the price of real estate.

Seventh, the circle rate in many places is lower than the market price. There is a need to gradually raise the circle rate. This can reduce the “facility” to absorb black money in purchasing properties. It also helps to reduce the stamp duty. Home prices will cool down.

CAPITAL GAINS TAX

Eighth, given the situation, there is a need to reduce, for some years, the capital gains tax on the sale of real estate, if the proceeds are invested in financial assets. So, some investors may choose to sell vacant properties. This increases the effective supply. This and some other policies suggested above can increase the fiscal deficit. However, the public authorities can sell the excessive land that they hold. This helps in raising funds. It also helps in increasing the effective supply of land.

Ninth, the ‘sell and build’ model is often used by builders in India as a way of financing a project, given the difficulties in borrowing for real estate development from banks and other financial institutions. There is a need then to liberalise, with safeguards, lending for real estate development. This can induce a gradual shift from the ‘sell and build’ model to the ‘build and sell’ model. This can reduce the risk and price for end-users.

Tenth, though the above policies can reduce home prices over time, homes can still be unaffordable for very many poor people. The public authorities need to intervene directly in this context with some schemes or subsidies.

In conclusion, appropriate policies can reduce, if not obviate, the need for short-term and costly palliative measures to reduce home prices.

The writer is an independent economist. He taught at Ashoka University, IIS (Delhi) and JNU.

The following is the article titled “Edelweiss MF’s equity, hybrid AUM crosses ₹1 lakh crore” as it appeared on page 7 of the sources:

Edelweiss MF’s equity, hybrid AUM crosses ₹1 lakh crore

Our Bureau
New Delhi

Edelweiss Asset Management Company (AMC) on Wednesday said its assets under management (AUM) in equity and hybrid assets have crossed the ₹1 lakh crore milestone.

“This achievement has been supported by strong consistency in performance of our equity and hybrid schemes and our robust distribution network,” Radhika Gupta, Managing Director and Chief Executive Officer, Edelweiss AMC, said in a media briefing. Further, she committed that it will offer differentiated product solutions and focus on delivering robust risk management and consistent returns for its investors.

Edelweiss AMC’s equity and hybrid AUM has grown by 70 per cent in FY26. In the same period, its folio count increased from 11.59 lakh to 15.7 lakh.

WEALTH CREATION

According to the fund house, the recent growth is primarily driven by its consistent focus on growing the focus on wealth creation through MFs and the increasing role of systematic investing in helping investors build wealth.

On an overall basis, as of June 29, the fund house managed assets across 47 schemes, including large-cap, mid-cap, small-cap, sector-specific and thematic funds. Its SIP book stands at around ₹690 crore, supported by a robust base of about 34 lakh active folios.

The fund house’s flagship products like Edelweiss Midcap and Arbitrage Fund managed assets of more than ₹5,950 crore, making it the largest in the category, according to the company.

The following is the article titled “‘Super El Nino threat, unseen since 1950, taking shape’” as it appeared on page 8 of the sources:

‘Super El Nino threat, unseen since 1950, taking shape’

RINGING A BELL. It may be one of the powerful events triggering fears of major worldwide weather and climate disruptions, says Australian bureau

Srikrishnan PC
Chennai

A potential Super El Nino is taking shape as warming in the tropical Pacific warming conditions reinforcing the event, says the Southern Hemisphere Monitoring Report of the Bureau of Meteorology Australia (BoM). Meteorological say it may become one of the most powerful El Nino events since 1950, triggering fears of major worldwide weather and climate disruptions.

A primary driver of the SSTs in the central tropical Pacific are above El Nino thresholds, and atmospheric indicators are also indicative of a potential Super El Nino. Ocean-atmosphere coupling has allowed the atmosphere work to reinforce the El Nino state and is likely to increase and keep El Nino going until at least the end of the year, says the report.

0.3°C WARMING

The latest relative Nino 3.4 index value (for the week ending June 28) is +1.24°C, comfortably above the El Nino threshold (+0.80°C) and warming by about 0.3°C from +0.94°C in mid-June. All global models are forecasting further warming of the tropical Pacific over the coming months.

Atmospheric indicators, such as trade winds, pressure and cloud patterns, are at levels consistent with El Nino. Trade winds were weaker than average over most of the tropical Pacific, cloudiness has increased near the date line, and the Southern Oscillation Index (SOI) is strongly negative. The latest 30-day SOI on June 27 was -25.2.

IOD OUTLOOK

The Indian Ocean Dipole (IOD) is neutral. The index is -0.02°C on June 27, 2026. Models indicate that a positive IOD event is likely during the southern hemisphere winter-spring. Model forecasts indicate a wide range in onset and peak intensity. A positive IOD can provide more moisture to India, often helping monsoon rain even in an El Nino year. El Nino is a natural phenomenon caused by variations in sea temperatures in the Indian Ocean. Its positive, negative and neutral phases can influence the Indian Monsoon.

WARNING SIGNS

Sea surface temperatures (SSTs) for the globe have been very warm, with May 2026 global SSTs the warmest May on record (since 1900), said the BoM report. Meanwhile, the Copernicus Climate Change Service (C3S), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the Copernicus Marine Service (CMEMS) have both confirmed that global SSTs reached record levels for the time of the year in April and May 2026. The C3S daily SST monitor shows SSTs slightly higher than 20.83°C in 2023 and 2024.

The Copernicus Marine Service says high temperatures contribute to the record levels seen since March 2024, reaching 21°C, reaching 21°C and reaching 21°C from 2023 and 2024 by 21st June.

BROAD IMPACTS

It is not yet clear if this exceedance is transitory or reflective of the coming months. While record-setting temperatures for this time of year are noteworthy, they are only at the beginning of El Nino, said the Copernicus report.

Warming oceans have broad impacts. They will keep the atmosphere warmer for longer, give more energy for more increase evaporation, all of which can lead to more rainfall and floods more likely. Warmer oceans also contribute to sea level rise and ice melt, and increases the stress on marine ecosystems.

Higher SSTs are also associated with more frequent and more intense marine heatwaves — periods of abnormally high water temperatures that disrupt ecosystems and impact coastal economies.

The following is the article titled “TN urges PM to modify VB-G Ram G scheme, give more say to State,” as it appeared on page 9 of the sources:

TN urges PM to modify VB-G Ram G scheme, give more say to State

Our Bureau
Chennai

Even as the TVK-led Tamil Nadu government indicated that it is on board to implement the new Viksit Bharat Gramin Rozgar Guarantee Mission (VB-G RAM G) scheme and earlier this week, Chief Minister Vijay on Wednesday requested Prime Minister Narendra Modi to consider some critical modifications to the scheme.

In a letter to the PM, he requested six key areas, including relaxation of funding patterns, State control over fund distribution, flexible work days, inclusion of State house construction, delegating authority to the State to notify wages, and a more vibrant grievance redressal.

GANDHI’S LEGACY

Vijay has also requested that the new scheme should carry the name Mahatma Gandhi, noting that he would honour his legacy and the significant contribution associated with the rural employment guarantee programme.

Earlier this week, the TVK government had indicated its intention to implement the VB-G RAM G scheme but requested the State, contrary to the Centre’s plan, have a bigger say in deciding who had rural employment scheme.

The new scheme replaces the UPA era Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA). While under MGNREGA, the Union government committed to providing funds, the VB-G RAM G operates under a 60:40 Centre-State cost-sharing model.

In its current form, the new scheme will result in a ₹12,642 crore scheme in Tamil Nadu, and with a 60:40 sharing for the Union and State governments, the former’s contribution will be ₹7,585 crore and the latter’s ₹5,057 crore.

ABRUPT SHIFT

“The VB-G RAM G operated under a different structure for state and central participation, and places an unsustainable burden on the state exchequer, which may reduce funding for other critical welfare schemes. I therefore, request that the 100 per cent funding be maintained for the wage and administrative components, with the material component shared on a 75:25 basis between the Government of India and the Government of Tamil Nadu,” Vijay said.

Commenting on the climate conditions, Vijay also suggested that based on advance notification, authority should be given to the District Collectors to notify the 60-day peak agricultural season as per local conditions.

State Housing Schemes under the VB-G RAM G scheme could also significantly accelerate achieving welfare targets and housing for all. “With these vital adjustments, the scheme can be executed with greater strategic vision, maximum local impact, and a sharper focus on rural empowerment,” Vijay said, seeking a favourable consideration of these proposals.

The following is the article titled “US limits on Mythos access keep foreign firms in limbo,” as it appeared on page 10 of the source:

US limits on Mythos access keep foreign firms in limbo

DIGITAL FORTRESS. Global users can access Claude 3.5, a model meant for broader release

Bloomberg

Foreign governments, companies and financial institutions were left in limbo after the Trump administration continued to restrict access to Anthropic PBC’s Mythos, a limited number of US-made AI models that the US government believes could possess advanced domestic and international intelligence models.

Global users can access Claude 3.5, a model similar to Mythos that is intended for a broader release, starting Wednesday, said the Claude maker on Tuesday. But talks with the US government continue over expanded domestic and international access to Mythos via the so-called Project Glasswing, it said. Mythos, a model Anthropic first previewed in April, is so powerful that the company limited access to a select group of vetted institutions to root out and patch cybersecurity vulnerabilities before making it more broadly available.

Washington’s move to restrict access to Mythos has highlighted how dependent the digital security of many US allies is on American silicon and AI innovation.

PROJECT GLASSWING

The US Department of Commerce is overseeing the project that grants access to Mythos. It requires that foreign governments and businesses meet the US Commerce Department imposed export controls on June 12, requiring Anthropic to obtain US permission before allowing any foreign national, company or institution, to access fable or Mythos. The US eased some of the restrictions on Mythos on Tuesday.

Anthropic is restoring access to its original set of Glasswing partners in the US and doesn’t have a timeline for when international partners will be included, said a company spokesperson.

Anthropic never released Mythos to the public, initially making it available to a small number of US tech firms, cybersecurity companies and banks to test out its capabilities. By early June, it added organizations in more than 15 countries that provide critical infrastructure services to Project Glasswing users.

The following is the article titled “$234 billion in enterprise software revenue model at risk from agentic AI: Gartner” as it appeared on page 10 of the source:

$234 billion in enterprise software revenue model at risk from agentic AI: Gartner

Our Bureau
Bengaluru

Agentic AI is set to disrupt enterprise software revenue models by causing the substitution of enterprise application software (SaaS) and creating arbitrage between now and next-gen pricing models. By 2030, this will account for roughly 20 per cent of enterprise application software (SaaS) revenue.

Agentic arbitrage occurs when AI agents complete tasks across multiple systems on a user's behalf, allowing users to interact with multiple traditional software interfaces via one AI.

“Agentic AI changes the economics of software,” said George Brocklehurst, Managing Vice-President at Gartner.

“Agentic systems deliver outcomes directly, bypassing traditional user interface (UX) heavy applications and complex workflows for users. This breaks the link between license count and revenue growth for many enterprise software vendors”.

SAASPOCALYPSE?

This shift is already underway and will refactor how software is built, priced and consumed.

“We are seeing the early destination of ‘SaaSpocalypse’, where the traditional revenue model of the big-spending software firms is being challenged today,” said Brocklehurst.

Experts feel that agentic AI can break the link between user counts and new revenue growth for many enterprise software vendors.

Gartner analysts said enterprise software vendors are facing a “structural risk”. “Enterprise buyers will demand more for less in terms of seats or dashboards,” said Brocklehurst.

“They want better outcomes and adding more AI features often creates more cost, not better outcomes. Vendors will need to acquire systems that retain deep institutional memory and customer context over time”.

Some vendors are already launching ‘outcome-based’ pricing that deliver autonomous results without user intervention, cross-system orchestration and lower customer context and deeper institutional memory. “As organizations increasingly want ‘outcomes’, the user interface is no longer a differentiator,” said Brocklehurst. “Legacy software revenue could be cannibalised by incumbents and taken by new entrants with more horizontally-aligned agentic platforms”.

Cyclical Fluctuations, Financial Frictions, and Firm Productivity Differences

 The core empirical observations documented in the sources center on the magnitude, pervasiveness, and cyclicality of productivity differences across firms, as well as their relationship with credit market conditions. These observations serve as the primary motivation for a model where financial frictions drive endogenous fluctuations in aggregate Total Factor Productivity (TFP).

1. Magnitude and Pervasiveness of Productivity Dispersion

The sources highlight that even within narrowly defined four-digit NAICS manufacturing industries, there are vast differences in productivity between establishments using the same measured inputs.

• The 90-10 Gap: A primary measure used is the "90-10 gap," which represents the percentage difference in productivity between an establishment at the 90th percentile and one at the 10th percentile in the same industry.
• Substantial Differences: The average 90-10 gap in U.S. manufacturing is approximately 100 percent, meaning a plant near the top of the distribution produces roughly twice as much output as one near the bottom from identical inputs.
• Widespread Phenomenon: These differences are not driven by outliers; the data suggests large within-industry productivity gaps are pervasive across the entire manufacturing sector.

2. Cyclical Variation of Productivity Gaps

A critical empirical observation is that this productivity dispersion is not static but fluctuates in sync with the business cycle.

• Widening in Downturns: The gap between high- and low-productivity firms tends to widen in years when GDP growth runs below average and is most visible during NBER-dated recessions.
• Narrowing in Expansions: Conversely, within-industry productivity dispersion tends to narrow when GDP growth is above average.
• Efficiency Implications: Because the spread of productivity widens and narrows over the cycle, the overall efficiency with which the economy uses its inputs—and thus aggregate TFP—also fluctuates.

3. Credit Market Co-movements

The sources also document how these productivity shifts co-move with credit market conditions, particularly loan delinquencies.

• Delinquency and Growth: Empirical data shows that delinquencies on business loans rise when GDP growth is depressed.
• Interest Rate Impact: There is a positive correlation between real interest rates and delinquencies; business-loan defaults tend to increase when real interest rates are high.
• Selection Margin: These observations support the model's mechanism where interest rates influence both the strategic default rate and the selection of which firms are productive enough to borrow and operate.

4. Significance for Aggregate Fluctuations

These empirical findings suggest that a significant portion of aggregate TFP is endogenous, rather than purely driven by exogenous "technology shocks".

• Misallocation: The sources argue these large, cyclically varying gaps are traced to financial frictions (adverse selection and moral hazard) that prevent capital from flowing to its most productive uses.
• Variance Contribution: Based on these empirical patterns, the authors' model suggests that the resulting misallocation accounts for approximately 30 percent of the variance of TFP at business-cycle frequencies.

The theoretical model framework presented in the sources is a tractable representative-agent model designed to deliver endogenous productivity fluctuations driven by financial frictions. It resolves the tension between powerful heterogeneous-firm models, which are difficult to solve, and standard business-cycle frameworks used to study aggregate fluctuations.

1. Dual Technology and Informational Frictions

The model endows each firm with two technologies: a production technology with idiosyncratic efficiency ($\omega$) that is private information, and a financial intermediation technology available to all firms. Two primary informational frictions drive the model's dynamics:

• Adverse Selection: Because a firm's idiosyncratic efficiency is not directly observable by investors, all firms receive an equal share of household savings regardless of their actual productivity.
• Moral Hazard: Firms with low productivity may find it more profitable to divert borrowed funds to an outside option (strategic default) rather than produce, which limits the borrowing capacity of even the most efficient firms.

2. Endogenous Sorting of Firms

The framework characterizes equilibrium by locating productivity cutoffs that sort firms into three distinct segments based on their realized productivity draw ($\omega$):

1. Lenders (Low $\omega$): Firms with the lowest productivity find it more profitable to deploy their intermediation technology, lending their funds to others at the prevailing inter-firm rate.
2. Strategic Defaulters (Medium $\omega$): Firms in the middle of the distribution borrow funds but choose to divert them to an outside option (government bonds) rather than produce.
3. Producers (High $\omega$): Firms with sufficiently high productivity borrow in the inter-firm market to purchase capital and produce goods.

3. Endogenous TFP and the Selection Margin

The central insight of this framework is that aggregate Total Factor Productivity (TFP) is endogenous. As macroeconomic conditions change, the cutoff points separating these three groups shift.

• Selection Effect: When conditions tighten and the productivity cutoff for producers rises, the economy "cleanses" itself of lower-productivity firms, concentrating production among the most efficient ones.
• TFP Decomposition: The measured Solow residual is decomposed into a standard exogenous technology shock ($Z_t$) and an endogenous prefactor ($\Phi_t$) that captures the changing composition of the producing cohort.
• Variance Contribution: This endogenous mechanism accounts for approximately 30 percent of the variance of TFP at business-cycle frequencies in the baseline model.

4. Role of Strategic Default

Unlike previous models that treat default as a "knife-edge" case or a result of involuntary insolvency, this framework incorporates strategic default as an equilibrium outcome. Strategic default serves a dual purpose:

• Amplification: It concentrates production among high-productivity firms more aggressively than models without a default margin.
• Stabilization: It acts as a buffer; when aggregate conditions shift, firms near the default threshold adjust first, which smoothes and stabilizes the dynamic path of the endogenous TFP response compared to models without default.

5. Tractability and Application

The model is highly tractable because the aggregate consequences of misallocation are captured by just a few objects: two cutoffs and an inter-firm interest rate. This allows the mechanism to be embedded as a "building block" in standard Real Business Cycle (RBC) models, enabling researchers to use off-the-shelf methods for estimation and policy analysis without tracking complex, evolving firm distributions over time.

In the provided source, financial frictions—specifically adverse selection and moral hazard—are identified as the fundamental drivers of capital misallocation and endogenous productivity fluctuations. These frictions prevent capital from flowing to its most productive uses, creating a link between credit market conditions and aggregate economic efficiency.

1. The Nature of the Frictions

The model framework is built around two primary informational barriers:

• Adverse Selection: Because a firm's idiosyncratic production efficiency ($\omega$) is private information, households and outside investors cannot distinguish between highly productive and less productive firms. As a result, every firm receives an aliquot (equal) share of household savings, regardless of their actual productivity.
• Moral Hazard: This friction arises because firms with low realizations of productivity may find it more profitable to strategically default by diverting borrowed funds to an outside option (such as government bonds) rather than using them for production. This possibility limits the borrowing capacity of even the most efficient firms, as lenders must price in the risk of diversion.

2. Financial Intermediation and Selection

To mitigate these frictions, the model introduces a secondary inter-firm lending market. In this market:

• Screening Technology: Lending firms utilize a screening technology that, while imperfect, allows them to identify and exclude firms with the lowest productivity from borrowing and defaulting.
• Endogenous Sorting: Firms sort themselves into three groups based on their productivity draws: lenders (lowest productivity), strategic defaulters (medium productivity), and producers (highest productivity).
• Credit Rationing: Because borrowers cannot credibly claim higher productivity to obtain more funds, credit is rationed, and all inter-firm financial contracts remain identical.

3. Frictions in the Context of Cyclical Fluctuations

Financial frictions cause the economy to respond dynamically to aggregate shocks through the selection margin.

• Interest Rate Impact: Fluctuations in the real interest rate influence the strategic default rate and the average productivity of the borrowing cohort. For instance, expansionary shocks can lower default rates by making production more attractive relative to the outside option.
• Countercyclical Dispersion: Data and model simulations show that productivity dispersion—the gap between high- and low-productivity firms—tends to widen in downturns and narrow when growth is above average.
• Strategic Default as a Stabilizer: The strategic-default margin serves as an "aggregator" that absorbs much of an aggregate shock's impact, stabilizing the dynamic path of productivity compared to models where default is not possible.

4. Impact on Firm Productivity and Aggregate TFP

The central finding of the source is that financial frictions make a significant portion of Total Factor Productivity (TFP) endogenous.

• Misallocation Cost: The presence of these frictions means the economy does not reach its "efficient limit," where all credit would flow to the single most productive firm.
• Variance Contribution: In the authors' baseline model, the misallocation resulting from these frictions accounts for approximately 30 percent of the variance of TFP at business-cycle frequencies.
• Cleansing Effect: When financial conditions tighten, the productivity "cutoff" for producers rises, effectively "cleansing" the economy of lower-productivity firms and lifting the average productivity of those remaining.

In the provided sources, endogenous firm sorting is the central mechanism through which financial frictions translate into aggregate productivity fluctuations. This process involves firms sorting themselves into different roles based on their idiosyncratic productivity draws, with the boundaries between these roles shifting in response to the business cycle.

1. The Sorting Mechanism: Three Firm Segments

The theoretical framework posits that each firm is endowed with a private production technology (with idiosyncratic efficiency $\omega$) and a common financial intermediation technology. Based on their realization of $\omega$, firms sort into three distinct groups:

• Lenders (Low Productivity): Firms with the lowest productivity ($\omega \leq \overline{\omega}_t$) find that the returns from their production technology are lower than the prevailing inter-firm interest rate. Consequently, they act as financial intermediaries, lending their funds to more productive firms.
• Strategic Defaulters (Medium Productivity): Firms in the middle of the distribution ($\overline{\omega}_t < \omega < \overline{\overline{\omega}}_t$) borrow funds in the inter-firm market but find it more profitable to divert those funds to an outside option (such as government bonds) and default rather than produce.
• Producers (High Productivity): Firms with the highest productivity ($\omega \geq \overline{\overline{\omega}}_t$) borrow funds to purchase capital and produce goods, as their production returns exceed both the cost of borrowing and the gains from strategic default.

2. The Role of Productivity Cutoffs

Characterizing the economic equilibrium reduces to locating the two productivity cutoffs ($\overline{\omega}_t$ and $\overline{\overline{\omega}}_t$) that demarcate these three groups.

• The lower cutoff ($\overline{\omega}_t$) is determined by an indifference condition where the expected return from production matches the return from lending.
• The upper cutoff ($\overline{\overline{\omega}}_t$) is determined where the marginal firm is indifferent between diverting borrowed funds and using them for production. A screening technology utilized by lenders prevents the least efficient firms from mimicking borrowers, thereby supporting the existence of a mass of lenders.

3. Sorting and Cyclical Fluctuations

These cutoff points are not static; they respond dynamically to aggregate macroeconomic conditions.

• Response to Shocks: During cyclical fluctuations—such as those triggered by aggregate TFP shocks, consumption shocks, or investment technology shocks—the boundaries between lenders, defaulters, and producers shift.
• Countercyclical Dispersion: In economic downturns, the spread between the most and least productive firms tends to widen. The model replicates this by showing how interest rate and output changes shift the cutoffs, reallocating capital across the firm distribution.

4. Impact on Firm Productivity and Aggregate TFP

The sorting of firms has profound implications for aggregate economic efficiency.

• Endogenous TFP: Because aggregate production is carried out only by firms above the producer cutoff ($\overline{\overline{\omega}}_t$), the economy's measured Total Factor Productivity (TFP) contains an endogenous component determined by the composition of this producing cohort.
• Selection Margin: Changes in financial conditions trigger a "cleansing" effect; for instance, a tightening that raises the producer cutoff forces less efficient firms out of production, concentrating activity among the most productive firms and lifting the average productivity of the active cohort.
• Quantitative Significance: The sources estimate that this sorting mechanism and the resulting misallocation account for approximately 30 percent of the variance of TFP at business-cycle frequencies. The strategic default margin specifically accounts for about one-third of that endogenous component.

In the provided sources, Total Factor Productivity (TFP) is a dynamic, multi-faceted variable that is central to understanding aggregate economic fluctuations. The authors move beyond the standard view of TFP as a purely exogenous "technology shock," arguing instead that a significant portion of measured TFP is endogenous, driven by the reallocation of capital across heterogeneous firms in response to changing credit conditions,,.

1. The TFP Decomposition: Exogenous vs. Endogenous

The sources define measured TFP (the Solow residual) as the product of two distinct components,:

• Exogenous Component ($Z_t$): This represents standard technology shocks that shift the productivity of all firms simultaneously,.
• Endogenous Prefactor ($\Phi_t$): This is the "selection margin," defined as the conditional mean of idiosyncratic productivity among producing firms,. Because financial frictions prevent the most efficient firms from operating at their full potential, this prefactor reflects the changing composition of the firms currently producing,.

2. Cyclical Variation and Productivity Dispersion

A core empirical motivation for the model is that within-industry productivity differences are both large and cyclically sensitive,.

• The 90-10 Gap: In U.S. manufacturing, the plant at the 90th percentile of productivity typically produces twice as much output as the plant at the 10th percentile using identical inputs,.
• Countercyclical Dispersion: This gap is not static; it tends to widen during recessions (when GDP growth is below average) and narrow during expansions,,. When this dispersion widens, the overall efficiency with which the economy uses its inputs—and thus aggregate TFP—declines.

3. Financial Frictions and Misallocation

The sources trace these TFP fluctuations to financial frictions—specifically adverse selection and moral hazard—that cause capital misallocation,.

• Adverse Selection: Because a firm's productivity is private information, investors cannot perfectly screen borrowers, leading to credit rationing where even the most efficient firms are limited in how much they can borrow,,.
• Selection Effect: When aggregate conditions shift (e.g., a rise in interest rates), the productivity "cutoff" for producers moves. A tightening of credit effectively "cleanses" the economy of lower-productivity firms, concentrating production among more efficient ones and lifting the endogenous TFP prefactor,.

4. Quantitative Significance

The sources highlight that this endogenous mechanism is a primary driver of macroeconomic volatility:

• Variance Contribution: Roughly 30 percent of the variance of TFP at business-cycle frequencies is endogenous in the authors' model,,.
• Role of Strategic Default: About one-third of this endogenous TFP component is specifically attributed to the strategic default margin,. By allowing firms to choose between production and default, the model captures a more aggressive concentration of production among high-productivity firms during shifts in credit conditions,.

5. Stabilizing and Amplifying Effects

Strategic default serves a dual purpose in shaping TFP dynamics. It acts as an amplifier by concentrating production among elite firms, but it also functions as a stabilizer for the dynamic path of TFP. By allowing firms near the default threshold to adjust first, the model produces a smoother and more persistent endogenous TFP response compared to models without a default margin, which often exhibit unrealistic oscillatory patterns,.

The assessment of the model's results focuses on its ability to match empirical data and its quantitative findings regarding the drivers of aggregate fluctuations. The authors conclude that their tractable framework successfully replicates key features of U.S. manufacturing data while revealing that a significant portion of productivity variation is endogenous.

1. Model Fit and Empirical Assessment

The model is evaluated based on its ability to match both targeted and untargeted moments from U.S. economic data between 1987 and 2021.

• Targeted Moments: Using the Simulated Method of Moments (SMM), the model successfully matches 10 out of 14 targeted second moments within sampling uncertainty. It accurately captures the variances of GDP, consumption, and delinquency rates.
• Untargeted Regressions: The authors perform OLS regressions on model-simulated data and find they reproduce the same signs as U.S. data: within-industry productivity dispersion narrows when GDP growth is high, and loan delinquencies rise when growth is depressed or real interest rates are high.
• Sign Consistency: Even for moments where the quantitative match is not exact (such as investment price correlations), the model correctly identifies the sign of the correlation in every instance.

2. Findings on Endogenous TFP Variance

A primary result of the model assessment is the quantification of the "selection margin" in driving aggregate productivity.

• Variance Contribution: The baseline model reveals that approximately 30 percent of the variance of Total Factor Productivity (TFP) at business-cycle frequencies is endogenous.
• The Default Margin: By comparing the baseline "two-cutoff" model to a "no-default" variant, the authors find that strategic default accounts for about one-third of this endogenous TFP component.
• Amplification vs. Stabilization: The results show that strategic default acts as both an amplifier, by concentrating production among elite firms more aggressively, and a stabilizer, by smoothing the dynamic path of TFP and preventing the unrealistic oscillations seen in models without a default margin.

3. Response to Macroeconomic Shocks

The model assessment includes an analysis of how firm productivity reacts to different aggregate shocks:

• TFP Shocks: An expansionary technology shock increases output immediately, but an endogenous TFP channel kicks in later. As the average return on capital eventually falls, the producer cutoff rises, "cleansing" the economy of less productive firms and narrowing the 90-10 productivity gap.
• Demand Shocks: Consumption and investment technology shocks raise interest rates, which increases borrowing costs and defaults. This forces production to concentrate among even more efficient firms, providing an "extra endogenous kick" to aggregate productivity.

4. Technical Robustness

The authors assess their solution method and find that a second-order perturbation is necessary for accuracy. While a first-order solution can lead to theoretical impossibilities (such as the two productivity cutoffs crossing), the second-order solution remains closely consistent with a fully non-linear perfect-foresight solution. This ensures the model's results regarding firm sorting and default remain theoretically sound during simulations.

Russian Offensive Campaign Assessment

 

Russian Offensive Campaign Assessment, June 30, 2026

The Kremlin continues to set unrealistic deadlines for the Russian military to complete the seizure of Donetsk Oblast that do not align with battlefield realities. Ukrainian President Volodymyr Zelensky stated on June 29 that the Kremlin has issued 15 separate deadlines for Russian forces to seize the entirety of Donetsk Oblast in total since 2022. Zelensky stated that the Kremlin gave five separate deadlines in 2022, including March 31, May 9, June 1, September 15, and December 31. Zelensky stated that the Kremlin gave Russian forces deadlines of March 1 and December 31 in 2023; March 1 and December 31 in 2024; September 1, December 1, and December 25 in 2025; and March 31, September 1, and now a deadline of December 31 in 2026.

Russian forces have repeatedly missed Putin’s demanded deadlines to seize specific territory in Ukraine, including Russian President Vladimir Putin’s early demand that Russian forces seize all of Donetsk and Luhansk oblasts by September 2022. The Kremlin’s deadlines for its military objectives continue to be divorced from the reality of Russian forces’ battlefield performance. Russian forced advanced on average 3.79 square kilometers per day in June 2026 — a rate far below Russian forces’ previous rate of advance in August 2025, when Russian forces advanced at a rate of 16.65 square kilometers per day. Russian forces still need to seize about 5,305 square kilometers to seize the remainder of Donetsk Oblast and are highly unlikely to seize the remainder of Donetsk Oblast by the newly set deadline of December 31, 2026. Russian forces have shown no ability to rapidly advance or restore operational maneuver in Donetsk Oblast.

These unrealistic deadlines for advance are contributing to Russian forces on the ground submitting “beautiful reports” up the chain of command, flag raising tactics, and Russian forces’ increasing use of (AI)-altered footage to claim advances in areas where Russian forces do not maintain positions. Russian forces continue to expend significant resources and manpower to try to fulfill these unrealistic objectives. Putin has likely developed a false perception of the Russian military’s successes and capabilities given the larger pattern within the Russian military of misrepresenting the battlefield geometry and providing inaccurate assessments. Zelensky’s comments on failed deadlines were likely in response to Putin’s June 28 claims that Russian forces are rapidly advancing across the theater and attempts to portray Russian victory in Ukraine as inevitable.

The Russian domestic population appears to be increasingly interested in the topic of the end of Russia’s war against Ukraine. Russian opposition source Meduza reported on June 30 that Yandex’s Wordstat service shows that there were over 137,000 search requests on Yandex asking when Russia will end its war against Ukraine from June 22 to June 28 – a record high since Russia launched its full-scale invasion in February 2022. Meduza reported that Yandex recorded a significant bulk of the searches in Moscow Oblast and St. Petersburg, Leningrad Oblast – regions where the Kremlin has prioritized installing air defense systems but largely failed to defend against Ukraine’s long-range strikes. The number of searches about when Russia will end the war has been growing for the second week in a row, with a previous peak occurring when Ukrainian forces struck St. Petersburg during the St. Petersburg International Economic Forum (SPIEF).

Polling from the Kremlin-linked Public Opinion Forum (FOM) from June 19 to 21 found that Russian President Vladimir Putin’s approval rating fell by five percentage points from 74 percent to 69 percent between June 12 and June 21, shortly after Ukraine’s largest strike on Moscow Oblast. Weekly FOM polling shows Putin’s trust rating consistently falling since February 2026. It is notable that FOM is acknowledging growing domestic discontent with Putin after over four years of war, suggesting the Kremlin has largely failed to isolate its constituents from the effects of Russia’s war effort.

Key Takeaways

1. The Kremlin continues to set unrealistic deadlines for the Russian military to complete the seizure of Donetsk Oblast that do not align with battlefield realities.
2. The Russian domestic population appears to be increasingly interested in the topic of the end of Russia’s war against Ukraine.
3. Ukrainian forces continued their long-range strike campaign against Russian military assets in Russia on the night of June 29 to 30.
4. Neither Russian nor Ukrainian forces made confirmed advances on June 30.

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Ukrainian Operations in the Russian Federation

Ukrainian forces continued their long-range strike campaign against Russian military assets in Russia on the night of June 29 to 30. USF Commander Major Robert “Magyar” Brovdi reported on June 30 that USF struck the Dubna Space Communications Center in Dubna, Moscow Oblast, overnight on June 29 to 30 – the second Ukrainian strike against the center since June 22. President Zelensky noted that the center is a special satellite communications facility used for reconnaissance and to coordinate Russian forces operating in Ukraine. Geolocated footage published on June 30 shows smoke rising from the center following the strike, and Moscow Oblast Governor Andrei Vorobyov acknowledged that Ukrainian drones damaged an administrative building in Dubna. Additionally, the Ukrainian General Staff reported that a June 28 strike against the Slavyansk Oil Refinery in Krasnodar Krai destroyed four tanks and damaged nine others, totaling 65,000 cubic meters of volume affected.

Russian Supporting Effort: Northern Axis

Russian forces continued offensive operations in northern Sumy Oblast on June 29 and 30 but did not make confirmed advances. A Russian milblogger posted a map claiming advances southwest of Sopych and into northern Marine, though this remains unconfirmed. Ukrainian forces continue to use drones and artillery to slow Russian advances, holding positions in Kindrativka and near Andriivka. A Russian milblogger claimed on June 29 that Ukrainian forces continue to hold their positions in Ryzhivka and are prioritizing striking Russian logistics routes toward Tetkino, Kursk Oblast.

Russian Subordinate Main Effort #1 – Kharkiv Oblast

Russian forces continued offensive operations north and northeast of Kharkiv City on June 29 and 30 but did not advance. Ukrainian officials reported that Russian forces are attempting to conduct infiltration operations in Hraniv but do not maintain any consolidated positions in the settlement. Russian forces appear to be attempting to tie down Ukrainian forces in certain non-priority areas of Kharkiv and Sumy oblasts to facilitate advances into northern Ukraine. Colonel Vitaliy Sarantsev stated on June 29 that Russian forces are attacking toward Kozacha Lopan with the intention of creating new limited offensive areas to prevent Ukrainian forces from moving force concentrations to priority sectors of the frontline. On June 29 or the night of June 29 to 30, Ukrainian forces struck a Russian drone control point near Veselaya Lopan, Belgorod Oblast. In the Velykyi Burluk direction, Russian forces continued limited offensive operations on June 30 without making confirmed advances.

Russian Subordinate Main Effort #2 – Oskil River

Russian forces continued offensive operations in the Kupyansk direction on June 29 and 30 but did not advance. A Russian milblogger implicitly refuted Putin’s June 28 claims of rapid advancement, stating that Russian forces are not advancing south of Kupyansk toward the Oskil River at the pace described in “public statements”. Russian forces also continued limited offensive operations in the Borova direction on June 29 and 30 but did not advance as Ukrainian forces counterattacked southeast of Borova.

Russian Subordinate Main Effort #3 – Donetsk Oblast

Russian forces continued offensive operations in the Slovyansk direction on June 29 and 30 but did not advance. Geolocated footage published on June 30 shows Russian Aerospace Forces (VKS) striking a Ukrainian position with a FAB-1500 guided missile in Mykolaivka. In the Kostyantynivka-Druzhkivka tactical area, the Russian MoD claimed that Russian forces seized Malynivka, and a milblogger claimed they seized Tykhonivka, though no confirmed advances were made on June 29 and 30.

Russian forces continue to deploy small, ill-equipped infiltration groups in an effort to accumulate behind Ukrainian positions in the Kramatorsk and Pokrovsk directions. In the Pokrovsk direction, Russian forces have stopped using armored vehicles due to the threat of Ukrainian drones. No confirmed advances were reported in the Novopavlivka or Oleksandrivka directions. Ukrainian forces are taking advantage of their drone superiority to undermine Russian efforts in the Oleksandrivka direction, disrupting logistics and forcing Russian forces to resupply positions using drones.

Ukrainian forces also continued an intermediate-range strike campaign against Russian assets in occupied Donetsk Oblast, striking an observation post near Staromlynivka and damaging gas stations in occupied Donetsk City. A Ukrainian strike on June 29 partially collapsed a bridge along the M-14 Rostov-Crimea highway near Novoazovsk.

Russian Supporting Effort: Southern Axis

Russian forces continued offensive operations in the Hulyaipole direction and western Zaporizhia Oblast on June 29 and 30 but did not make confirmed advances. The Russian MoD continues its cognitive warfare effort to exaggerate Russian advances northwest of Hulyaipole, claiming the seizure of Rivne and Lisne contrary to available evidence.

Ukrainian forces struck a road bridge near occupied Azovske and drone control points near Myrne, Luhove, and Skelky. In occupied Crimea, Ukrainian forces struck a railway bridge near occupied Ichki, four electrical substations in occupied Kurman and Dzhankoi, and a fuel train in occupied Feodosiya. These strikes are increasingly causing power outages in occupied Crimea, leading occupation authorities to order a temporary power supply restriction regime in Sevastopol.

Russian Air, Missile, and Drone Campaign

Russian forces conducted a series of long-range drone strikes against Ukraine on the night of June 29 to 30, launching 154 drones. Ukrainian forces downed 138 of these drones. Russian strikes left consumers in Dnipropetrovsk, Zaporizhia, Sumy, Kharkiv, and Chernihiv oblasts without power. Russian forces are also increasingly striking gas stations in Ukraine as part of a concerted campaign aiming to replicate the effects of Ukrainian strikes on Russia’s fuel infrastructure.