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Updated: May 22, 2026 at 2:52 AM

The EconoScope Journal

💸A journal of economic thought — written by learners, for learners. ✍️From global crises to quiet theories, all in English. ✅The Journal works with @oeconomicus – the MGIMO Economics Club

@econoscopejrnl is a growing community focused on learners and global and related topics

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The EconoScope Journal

May 22, 2026, 02:52 AM

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📈 Prospects of Anthropic IPO

Claude is a strong frontier AI model for coding, complex tasks, automating workflows and generating high-quality texts. Anthropic, the startup behind Claude, may consider an IPO (Initial Public Offering; based on Reuters report) in Q4 2026.
The following factors may influence the potential IPO.

What public investors might like about Anthropic:

1. The company does not longer sell only access to Claude. It monetizes through API usage, enterprise plans, distribution through AWS (Amazon Web Services), Google Cloud and Microsoft Azure, as well as vertical products for finance, education and government;
2. ✴️ Although Claude has been on the market for only 3 years, it has already been adopted by a large number of business customers. This fact strengthens company’s position on the market;
3. 🖥 Newly released “Mythos” suggests that Anthropic is capable of developing cutting-edge technology. Although the model is available only to a limited number of firms, talks and available information about its capacities greatly increased the company’s visibility in public disclosure even before the public release of Mythos. What is more, tightly controlled frontier models may increase enterprise trust, which allows for higher pricing, large contracts and strategic deployments.

However, Anthropic faces some problems:

1. 💻 Creating high-end gated LLMs like Mythos is great for valuation, but it does not help with short-term profits. Developing and maintaining such models takes a lot of resources, and Mythos probably won’t be monetized for some time because access remains restricted to a number of selected companies;
2. High run-rate revenue of Anthropic is a positive signal, but it is not the same as audited recurring revenue and may change, hence the success depends on Anthropic performance in the coming months;
3. ✴️ Anthropic may face additional competition for investor attention if OpenAI goes public at approximately the same time, which could affect pricing and post-list performance. Additionally, OpenAI has greater public visibility and probably more resources for PR and investor communications;
4. The company disclosures limited financial information at the moment. If it proceeds with an IPO, it would have to reveal more about revenue composition, costs, risk factors, governance, etc.
5. ✴️ Anthropic relies on a small number of partners for its critical infrastructure. Of course, Amazon, Google and Microsoft are credible enterprises, but dependence on few companies makes Anthropic vulnerable towards
changes in prices, policies or contracts and lowers its bargaining power.

💸 Overall, these are some of the factors that may affect the timing, valuation and market reception of an Anthropic future IPO. If the company does not rush going public (as it probably is currently), it could pursue one of the largest AI-related public offerings in the market.

Written by Mikhailov Dmitry (1-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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🇺🇸⚡️Crisis in the Middle
East and its Impact on the US Economy

🚨The recent conflict in the Middle East has affected not only Iran, Israel, and other countries in that region but also the whole world. The closure of the Strait of Hormuz, through which almost 20% of the global oil pass, caused oil prices to exceed US$100 per barrel and, as a result, led to a new energy crisis that had a great impact on the US economy.

⛽️The first good which price increased considerably was gasoline. Since the beginning of the conflict, its prices have exceeded US$4.00 (per gallon), compared to approximately US$2.98 (per gallon) just before the beginning of the hostilities.

📈Diesel prices have also risen by around US$1.70, impacting transport costs. As a result, prices of groceries and other goods increased dramatically: the consumer price index jumped 3.3%, reflecting higher costs of energy caused by disruptions in the Middle East.

🗽What’s more, some economists consider the further risk of stagflation in the United States significant in 2026. The combination of high inflation, especially due to rising energy prices, and slowing economic growth creates conditions that are similar to the 1970s, when the world economy faced a major crisis as well. The key risk factors are considered to be geopolitical tension and risky monetary policy.

🏜️To conclude, rising prices on oil, caused by the closure of the strait of Hormuz, have influenced the economy of the USA considerably. The US citizens have been forced to put up with the increasing prices of vital goods and gasoline. Right now, USA authorities have to deal with the growing pressure in society and stabilize the economy at the same time.

📝Written by Ulyana Erofeeva 1-IIEPD

The EconoScope Journal

May 22, 2026, 02:52 AM

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The EconoScope Journal

May 22, 2026, 02:52 AM

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🔍 The SDG Trap: why chasing all 17 goals at once can backfire

The UN's 17 Sustainable Development Goals (SDGs) were designed as an indivisible blueprint for 2030. But in practice, pursuing one goal often undermines another. Growth (SDG 8) can kill climate action (SDG 13). Food security (SDG 2) can destroy biodiversity (SDG 15). The result? Only 18% of SDGs are on track.

So how do countries choose what to prioritize? Here's the reality.

📍 3 ways countries navigate SDG trade-offs

1. National context decides everything. A poor landlocked country needs jobs first. A Pacific island needs survival first.

🔹 Russian Arctic: climate action (SDG 13) and innovation (SDG 9) are top priorities. "Zero Hunger" (SDG 2)? Almost irrelevant there.
🔹 Tonga: renewable energy for youth isn't a nice-to-have — it's a lifeline.

2. Data reveals hidden leverage points. Stop ticking boxes. Instead, model which goals unlock the rest.

🔹 China study: only 11.9% of targets needed urgent action (mostly biodiversity). One quarter faced systemic barriers — especially SDG 12 (responsible consumption). Fix those bottlenecks, and the system moves.

3. «Leave No One Behind» as the hard limit. GDP growth can hide suffering. If the poorest lose land while the economy booms — have you really developed?

🔹 Mexico: now embeds gender equality and indigenous rights directly into its climate policies. A green transition shouldn't crush the vulnerable.

📎 A real-world example: China's 2025 priority model analyzed cascading impacts across all 17 SDGs. The finding: most targets don't need immediate action. But biodiversity collapse and land degradation do — and without fixing SDG 12 (consumption), nothing else works. That's not a checklist. That's systems thinking.

The bottom line is that the SDGs aren't failing. The political economy of choice is hard. No universal formula exists. But transparency, data, and «leave no one behind» get you much further than pretending all 17 goals are equal.

#econoscope_countries

Written by Elmira Miftakhutdinova (2-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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🔍The Minsky Moment Concept: What is it?

A Minsky Moment is a sudden collapse of market conditions following a prolonged period of speculative growth. The key idea is that financial stability is destabilizing: the longer the market remains calm, the greater the accumulated risks, which inevitably lead to a crisis.

📍5 Stages of Crisis Development (Minsky Cycle)

1. Initial State: (Hedge Finance)

After the previous recession, entities exhibit low risk appetite. All debt obligations are secured by current cash flows. Borrowers are able to pay both interest and principal. The market is in equilibrium.

2. Speculative Finance

Favorable conditions generate excess confidence. Agents begin borrowing for projects where cash flow only covers interest payments, but not the principal. Refinancing becomes a constant necessity. The system becomes vulnerable to changes in interest rates.

3. Ponzi Finance

The final and most risky stage. The borrower's current income is insufficient even to pay interest. The only source of debt servicing is the constant rise in asset prices. The borrower relies solely on reselling the asset to the "next" market participant at a higher price.

4. Trigger

Any event that increases the cost of borrowing or reduces liquidity (an increase in the Central Bank's key interest rate, a drop in household income, a geopolitical shock). Asset prices stop rising.

5. Minsky Moment (Collapse)

Ponzi-type borrowers are unable to meet their obligations and begin a massive sell-off of assets.
Asset prices fall sharply, revealing the capital deficit of "speculative" borrowers.
Banks curtail lending ("credit famine").
Even conscientious borrowers (Hedge Finance) are losing income due to the general recession and defaulting.

📎An example from economic history

The most striking empirical verification of the concept occurred in 2008 (the Global Financial Crisis):

1. 1990–2006: Easy money policy, subprime mortgage lending (NINJA loans).
2. 2007: The US Federal Reserve's key interest rate increased.
3. 2008: Real estate prices collapsed—holders of mortgage-backed securities (CDOs) were unable to refinance them. The "Minsky Moment" occurred, leading to the bankruptcy of Lehman Brothers.

Written by Ilyana Khalinginova (2-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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Can generative AI hit the ceiling?

✴️ Modern generative AI in the form of deep neural networks, or LLMs (Large Language Models) have developed rapidly since 2018, when GPT-1 was created. 4 years later ChatGPT was introduced by OpenAI. Sam Altman’s company has been expanding swiftly ever since and it was announced on March 31, 2026 that it had closed a funding round at an $852 billion post-money valuation, but there is one major issue - scaling.

The more computing power is used, the less are the marginal returns from adding it.

🖥 For example, OpenAI’s CFO Sarah Friar reported that their “available compute” grew from 0.2 GW in 2023 to 0.6 GW in 2024 to almost 2 GW in 2025. This does not seem as a problem at first, but according to IBM CEO Arvind Krishna it takes around $80 bil. to build and fill 1GW data center with IT equipment, so increasing computing power is really expensive. Additionally, such data centers need to be maintained by whole teams of engineers, plumbers, electricians, etc. Electricity costs alone may have risen from ~$200 mil. to around $1.947 bil. annually. *

The more data AI is trained on, the less the same amount of data impacts the results.

💸 Those costs don’t matter much if the revenue covers it. By investing in data-centers, companies improve their AI models and profit from selling subscriptions or helping other firms create LLMs - that is how it has been for many years. Now such models are getting close to hitting the ceiling because the research finds diminishing returns from adding compute power. Further large improvements will probably require a model to be trained with much more hardware than it has been trained on, hence the same amount of computing power which was used to train a LLM even 3 years ago is not nearly enough nowadays.

The more data AI uses, the less quality human-made texts remain.

✏️ Another unexpected issue which may lead to a lack of improvement in AI is the shortage in data. This problem has appeared recently because companies are running out of new high-quality information to train their models on. This issue is the same at its core as the hardware problem: the more complex the models get, the more data they need to progress. Researchers state that under current trends, public human-generated text may become a bottleneck in 2026-2032.

📈 There are many factors that can slow down or speed up the progression of neural networks, like Google’s new algorithms that can increase NVIDIA H100 GPUs’ performance by up to 8x and reduce KV-cache memory by at least 6x in some tasks. However, it is clear that scaling on its own is becoming less efficient and future progress may rely on other methods.

*Illustrative scenario cost based off rough calculations. Electricity cost was calculated for 24/7 total facility load with PUE=1.3, becoming 1.9*1.3=2.47GW=21.6372TWh. With electricity cost approx. to 9cents/KWh, the total is $1.947 bil.
Written by Mikhailov Dmitry (1-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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As we develop our rubric dedicated to entrepreneurs, we decided to dive into transport logistics.
Today we’ve interviewed the CEO of the UTLC ERA - Alexey Grom. The company is the leader in the railway transportation market.
Alexey Grom told us about the factors that defined his career choice, the decade-long history of the company, the advantages that the company has, the set of destinations and directions, innovative solutions and so on. We talked about accomplishing goals no matter the opinion of the others and the significance of the true team spirit. Finally, Alexey Grom gave a piece of advice to students who embark on their professional journeys.
The interview turned out to be inspiring and informative! Read the whole interview below 👇

🗣️ Interviewed by Vasilisa Shevchenko (1-IITSD)

🖼️ Designed by:
Dmitrii Mikhailov (1-IER)
Vera Zhukova (1-IER)
Mikhail Maksimov (2-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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#econoscope_history

🚗The Oil Crisis of 1973-1974

🛢️The Beginning of the Crisis
OAPEC (Organisation of Arab Petroleum Exporting Countries) implemented a punitive embargo against countries that provided political or military support to Israel, during the Yom Kippur War in 1973, including Canada, Japan, the Netherlands, the United Kingdom, and the United States. The restrictions were later extended to Portugal, South Africa and Rhodesia*. The sanctions blocked petroleum exports and imposed restrictions on oil production.

⛽Oil Scarcity in the US
The petroleum embargo occurred alongside dollar devaluation placed additional strain on an American economy, that was growing dependent on foreign oil supplies. The cost of oil escalated dramatically, quadrupled from $3 to $12. President Nixon’s administration introduced a new strategy to increase domestic oil production and reduce reliance on foreign fuel. Consumers waited in long lines during the gas shortage. Buyers rushed to buy fuel-efficient Japanese cars, hurting U. S. automakers. The administration enforced a national 55 mph speed limit to save fuel.

📉Outcomes
On November 7, 1973, the Nixon Administration unveiled Project Independence, a policy designed to achieve energy self-sufficiency by 1980. Washington initiated parallel negotiations with Egypt, Syria, Israel and key oil producers in pursuit to end the embargo. Early discussions between Henry Kissinger and Arab leaders focused on the Israeli disengagement from Sinai and the Golan Heights began in November 1973. The January 18, 1974, Egyptian-Israeli disengagement pact did not constitute a final peace agreement, nevertheless, OPEC concluded the embargo in March 1974. On December 22, 1975, a Strategic Petroleum Reserve (SPR) was established, that could replace 3 months of oil import in the event of supply disruptions.

*Rhodesia - self-declared independent state in Southern Africa from 1965 to 1979 (current Zimbabwe)
✍️ Written by Barkov Mark (1-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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📈The origins of Bitcoin and its Mysterious creator

Bitcoin is often described as the first successful decentralized digital currency. Its creation, however, is shrouded in mystery. To understand Bitcoin's significance, it is essential to look back at the circumstances of its birth and the enigmatic figure behind it.

Historical context

✅Bitcoin emerged in the aftermath of the 2008 global financial crisis. Trust in traditional financial institutions had reached a historic low. Governments and central banks were intervening to rescue failing banks, prompting widespread debate about the stability and fairness of the existing monetary system.

It was in this climate of uncertainty that a new idea began to take shape—one that proposed an alternative to government-issued currency and centralized financial intermediaries.

The White paper

On October 31, 2008, an individual or group operating under the pseudonym Satoshi Nakamoto published a white paper titled «Bitcoin: A Peer-to-Peer Electronic Cash System.» The document was posted to a cryptography mailing list and outlined a system for transferring value directly between parties without relying on a financial institution.

👨‍💻The paper proposed a combination of existing technologies—cryptography, proof-of-work, and distributed networks—to create a system where transactions could be verified collectively by participants rather than by a central authority.

The Launch

📰On January 3, 2009, Satoshi Nakamoto mined the first block of the Bitcoin network, known as the genesis block. Embedded in the code of that block was a headline from the British newspaper.

"Chancellor on brink of second bailout for banks."

The inclusion of this headline has been widely interpreted as a commentary on the fragility of the traditional banking system and a subtle indication of the motivation behind Bitcoin's creation.

🛜Shortly thereafter, Satoshi released the open-source software, allowing others to join the network, validate transactions, and begin mining new blocks.

The disappearance of Satoshi Nakamoto

📞For approximately two years, Satoshi remained active in the Bitcoin community corresponding with developers via email, contributing to forums, and refining the code. During this period, Satoshi's communications were characterized by a measured, technical tone.

⌨️In 2011, Satoshi Nakamoto gradually reduced their presence. The final confirmed communication from Satoshi was an email sent to a fellow developer in April of that year, stating that they had moved on to other things.

🤔Since then, Satoshi has not made any public appearances or communications. Despite extensive speculation and investigative efforts, the true identity of Satoshi Nakamoto remains unknown. It is unclear whether Satoshi is a single individual or a collective, and no conclusive evidence has emerged to resolve the mystery.

Written by Yakha Baiduyeva (2-IER)

The EconoScope Journal

May 22, 2026, 02:52 AM

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#econoscope_countries

China’s economy: key features and current dynamics

🇨🇳China’s economy combines rapid industrial capacity, strong state influence, and accelerating technological ambition. After decades of export- and investment‑led growth, the country is pursuing a transition toward a more balanced model that aims to emphasize domestic consumption, services, and innovation. Manufacturing remains a backbone—China is a global hub for intermediate and finished goods—but policy now seeks higher‑value production and supply‑chain resilience.

🏭State‑owned enterprises (SOEs) and an active industrial policy play a central role. The government steers credit allocation, major infrastructure investment, and strategic sectors (telecoms, energy, semiconductors), using tools from fiscal stimulus to targeted subsidies. At the same time, a dynamic private sector—from small manufacturers to tech giants—drives most employment and innovation, creating a mixed public‑private landscape.

📈Macro characteristics include historically high savings and investment rates, ongoing urbanization, and substantial foreign exchange reserves. Persistent challenges are demographic headwinds (an aging population), a large and leveraged property sector, and rising corporate and local government debt. Financial regulation has tightened in recent years, aiming to rein in shadow banking and speculative credit while preserving growth stability.

🌐China prioritizes technological self‑reliance and digital adoption—AI, 5G, and advanced manufacturing are policy focal points—while expanding global economic influence through trade and infrastructure initiatives. Environmental pressure has spurred greener industrial targets, though transitioning still requires significant structural change.

💴Overall, China’s model is pragmatic and state‑directed, blending market mechanisms with centralized planning. Its near‑term outlook hinges on the pace of domestic demand recovery, property market stabilization, and successful upgrading of industry and technology amid global geopolitical and supply‑chain shifts.

✍️Written by Vera Zhukova 1-IER

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