A graphical summary of chokepoints in global trade

After China’s rare earth minerals export restrictions and Iran’s blockade of the Strait of Hormuz, chokepoints in international trade have become a hot topic. Never mind that the biggest chokepoint in the world economy has long been the US stranglehold through the threat of sanctions. 

Martin Wolf has an excellent oped that illustrates the importance of the Strait of Hormuz.

I have used it as an opportunity to do a deep dive into chokepoints using Claude AI. 

Among maritime routes, the Strait of Malacca stands out as the most important chokepoint in terms of sheer volume. The Panama Canal is critical for the US. 

The table below maps each chokepoint across eight dimensions. Note that the Turkish Straits punch above their weight. While it carries only 3% of global seaborne trade, that includes around 20% of global wheat exports from Ukraine, Russia, and Romania, making them a food security flashpoint. The Taiwan Strait is classified as "critical (latent)", with 40% of the world's container fleet passing through it, and any escalation would instantly cascade through semiconductor and electronics supply chains globally.

This is a list of alternative routes and their respective detour costs. As can be seen, there is no viable alternative to Hormuz for Gulf states. A closure is modelled to push oil prices to $120–150/bbl.

Among companies, ASML (monopoly in EUV lithography machines), TSMC (64% of global pure play foundry, and almost all 3 nm and 5 nm), and Nvidia (92% of data centre GPUs) are standout corporate chokepoints. China, for materials and several inputs to manufacturers globally, stands out as the foremost national chokepoint. However, the mother of all chokepoints may perhaps be the SWIFT money transfer system controlled by the US. 

There are nine corporate chokepoints. The Western chokepoints tend to be policy-leveraged through export controls and sanctions. The Chinese chokepoints are leveraged through state-controlled industrial policy and export licensing. 

The hardest substitutability problems aren't the ones with the highest market shares, but those with the longest replacement timelines. ASML and heavy rare earths both require over ten years to replicate at scale. 

Let’s now examine India’s external vulnerabilities. India’s most acute dependencies are in the sectors of energy & fertilisers, pharmaceuticals, critical minerals & battery materials, and electronics & semiconductors, with China being the chokepoint country in all but the first. 

In defence, while India’s dependencies have grown more diversified, the vulnerabilities are widely known. The hidden defence vulnerability is naval gas turbines from Ukraine's Zorya-Mashproekt, and rare earth magnets used in radars and missile guidance - both of which sit on geopolitical fault lines. 

The pattern of leverage shows a sharp dichotomy: India's strategic vulnerability is concentrated in two countries - China (electronics, pharma APIs, rare earths, critical minerals processing, batteries) and Russia (oil, defence, fertilisers) - while its geographical chokepoint exposure sits at Hormuz, Bab el-Mandeb, and Malacca. The most acute vulnerabilities feature single companies as well: TSMC for advanced chips, CATL for batteries, Saudi Aramco/ADNOC for Gulf oil.

So how can these vulnerabilities be mitigated?

The table below has the proposed diversification measures categorised into three: short-term (focused on supplier diversification, strategic stockpiles, and emergency tariff calibration), medium-term (activate PLI schemes, trade agreements, and government-to-government deals (Saudi DAP 5-yr contract, Argentina lithium, Australia rare earths), and long-term (aim for genuine strategic autonomy). 

In conclusion, like any other economy today, small or large, India cannot eliminate dependencies. But it can change the politics of dependency by making suppliers compete and by retaining genuine substitutes for each input. The most successful precedent is the SIPRI defence data showing Russia’s share collapsing from 72% to 36% in just a decade, achieved through sustained policy effort and friend-shoring.

Some thoughts on the RBI's exchange rate management policy

The pressure on the rupee in the aftermath of the Gulf War has generated considerable attention and discussion. I have blogged here on the implications of the Gulf War on India’s external account. 

This may also be a good time to examine the dynamics driving the rupee downward. The rupee’s weakness is nothing new. Since the beginning of 2025, the rupee has been the weakest-performing EM currency, behind only the Turkish lira. As reported here, the rupee has weakened from 107 in early 2025 to 92 in the 40-country trade-weighted real effective exchange rate index, despite the RBI intervening heavily to backstop the decline. In fact, since October 2024, foreign investors have pulled out at least $45 billion, and their shareholding in Indian equities is currently at a 15-year low.

The graphic shows that the rupee held steady for two years, from at least the beginning of 2023 to the end of 2024, on the back of rupee purchases to prevent it from depreciating and find its level. In fact, compared to an annual USD-INR volatility of 5% in the 2000-22 period, the INR-USD volatility fell to just 1.8% during this period, the lowest in over 20 years, lower even than the 2000-2004 period when INR was effectively pegged! 

This drastic volatility suppression, combined with India’s higher inflation (CPI averaging ~5%) vs trading partners (2-3%), produced the biggest REER overvaluation build-up in the emerging-market universe during this cycle. The rupee’s 40-currency REER (base 2015-16) peaked at 108.14 in November 2024, and since then has depreciated sharply to below 95 by March 2026. This depreciation has been far in excess of any peer.

Similar trend is visible with respect to USD too. The rupee stands out for its unique flat trajectory through 2022-24 even as peers depreciated substantially in response to the Fed tightening cycle. However, since Oct 2024 the rupee has depreciated steeply, overtaking several peers.

It becomes clear that the rupee was held artificially overvalued for over two years. This, by itself, should have been reason enough that pressure mounted for a corrective depreciation. In addition, there was the pressure from the spike in oil prices (and associated worsening of the external account, already weakening from the tariffs and FPI repatriation) and the general trend of risk-off and capital flight to the safety and liquidity of the dollar. 

By itself, the Gulf War would have put enough pressure on the currency. But its combination with the stress built up due to the forced overvaluation amplified the capital flight induced by the Gulf War, thereby exacerbating the pressure on the rupee and worsening the depreciation when it happened. 

The table below is a quantified decomposition of what drove the 11.9% depreciation. It shows two alternative decompositions at the peak (Mar 2026), which capture the overshoot moment, and at current levels (Apr 2026), after partial reversion. 

At peak (Mar 2026), the biggest driver by far was the overvaluation correction (63% of the fall), which is the “hidden cliff” the RBI’s peg concealed and which was unique to the rupee. The general market volatility (36%), experienced by all peers, was a secondary driver, reflecting genuine dollar/EM repricing. The net overshoot, at least till now, has been negligible.

Has there been a Dornbush overshoot? Rudiger Dornbusch's 1976 overshooting model predicts that when exchange rates are flexible, but goods prices are sticky, a monetary or policy shock causes the exchange rate to overshoot its long-run equilibrium before reverting. In simple terms, if the currency has been artificially propped up, the "stickiness" is extreme, and therefore, when the adjustment finally comes, the overshoot magnitude is larger than in a regime of continuous flexibility. However, the Dornbusch overshoot and reversion are not yet visible. The reversion might happen in the coming weeks.

So what are the lessons?

By maintaining the rupee as a de facto pegged currency from 2023 to October 2024, the RBI accumulated an 8% REER overvaluation that had to be corrected. When the regime shifted — Trump election, FPI outflows, US tariffs, Iran war — the correction was both deeper and faster than peers experienced, precisely because the catch-up component (8pp) was additive to normal drift (3.8pp). The rupee is now at or near its new equilibrium of ~94-95, down 11.9% from Oct 2024.

The RBI’s 2022-24 intervention pattern - buying ~$400bn in forex reserves while keeping the rupee rigid - converted exchange-rate risk into reserve-allocation risk. When the regime shifted, reserves fell by $80bn in four months without preventing the correction. Further, the sharp Mar 2026 overshoot caused imported inflation, margin stress on exporters who had hedged at 84, and a sudden repricing of corporate foreign-currency debt. A gradual depreciation path through 2023-24 (releasing 3% per year against the peer-consistent rate) would have spread this adjustment at much lower systemic cost. The rupee has done exactly what a freely-floating currency would have done gradually over 3 years, but compressed into 18 months because the peg delayed adjustment, and with serious credibility cost (for investors). 

The speed of adjustment was consistent with Dornbusch dynamics (7.2% in a single month from Feb to Mar 2026 is unprecedented for INR). However, the second half of the Dornbusch pattern - reversion toward long-run equilibrium - has not so far materialised, though it could yet in the coming weeks. The rupee is currently 94.10, only 0.8% below its 94.86 peak. This is within noise, not meaningful reversion. 

This is a teachable moment on currency management for central banks. Policies that keep a currency overvalued are always counter-productive, especially for developing countries that are always at risk of being caught in an episode of sudden stop and capital flight. When such episodes are triggered, the overvalued currency invariably experiences a steeper slide and greater overshoot, with all attendant consequences. Most importantly, steep devaluations convey a macroeconomic instability signal to investors. It increases the country risk for investors, who must now factor in the likelihood of episodes of sharp depreciation risks while making their investments. It is a dent in the central bank’s credibility. 

The rupee is going through one such episode. The original sin may have been committed in the 2023-24 period. 

Impact of policy interventions and shocks on India's economic growth

The sustainable growth rate of any economy is that which strips out the positive effects of the government’s fiscal interventions and the negative effects of economic shocks. This blog has held that, given its deficient human, physical, and financial capital, India’s neutral growth rate is about 5-5.5%. 

This post provides a framework to figure out the underlying economic growth rate by stripping these positive and negative contributors. 

So, what has been India’s underlying neutral (stripped of the impact of policy interventions) economic growth rate? 

Answering this requires us to identify the specific interventions and events that have contributed to the positive and negative shocks, and to try to figure out their respective economic impacts. 

In the last decade or so, the economy has faced three large negative shocks: demonetisation, the introduction of GST and associated efforts to formalise the economy, and the pandemic. In addition, on the external front, it has faced the oil shocks from the Ukraine and Iran wars, and the Trump tariffs. 

The economy as a whole has benefited from three fiscal events - corporate tax rate reduction, income tax rate reduction and rationalisation, and the GST rate reduction. 

While it is now clear that the government suffered revenue loss from the corporate tax rate reduction, the income tax rate reduction, and rationalisation appear to have boosted the tax base and increased revenues. It appears (at least for now) that the existing corporate tax rate was on the left side of the Laffer curve, whereas the direct tax rate was on the right side. 

The government clearly benefited from three positive fiscal events: the long period of low oil prices (increased excise tax revenues due to not passing through the reduced oil prices), the surge in RBI dividends, and the large additional fiscal space from discarding the FRBM framework. 

The net boost to fiscal balance resulted in a sharp spike in capital expenditure. It is to the credit of the government that it eschewed the subsidies and revenue expenditure route. This increase in capex includes taking on the budget account capital expenditures of NHAI and Railways. In addition, there has been the introduction of the zero-interest 50-year loan to state governments under the Special Assistance to States for Capital Investments (SASCI). 

What have been their respective contributions to the output growth? Here is a graphical summary.

This table captures a brief description of the assumptions and estimations used. 

On the positive boosts to the government’s fiscal position, the contributions of the three factors are shown below. 

On the capital expenditure side, the government assumed in the budget the expenditures on railways and highways. 

The fifty-year interest-free loan to states under SASCI was a new addition, amounting to about Rs 1.5 lakh Cr each year. 

This explains how the increase in capex could be disaggregated and distributed among the different parts discussed above. 

The disaggregated impact of the positive and negative factors on the economic output is shown below. 

Based on the above, the underlying neutral economic growth appears to be in the range of 5-5.5%.

Clearly, since the pandemic, policy interventions have played an important role in boosting the economic output. 

The important point here is that while policy interventions may have boosted economic growth for some time, it remains to be seen in the coming years whether they have shifted the economy onto a higher underlying steady state growth trajectory. This is especially important since the headroom for further interventions, like fiscal space for more capex or tax cuts, may have shrunk, and we may be entering a world of increasing uncertainties and headwinds for the foreseeable future. 

In the final analysis, the balance sheet of the policy interventions will boil down to this question. Did the fiscal transfers of the last few years create the conditions (by broadbasing economic growth or increasing capital accumulation, for example) for a shift to a higher trajectory of growth, or was it a case of merely providing a temporary boost to the national output?