RBI's Real Rate Mistake — and the Two Bad Choices Iran Just Handed India

He opens by promising to close the medium-term unit “in another 10 minutes,” and does — the equation gets one more quick pass for anyone who missed it, the Friedman story gets a two-minute recap for latecomers. Then Prof. Tantri spends the rest of the session doing something this series hasn’t seen him do quite this way before: pointing the whole Phillips-curve-and-real-rate apparatus at India’s actual policy stance right now, live, with real numbers — RBI’s rate cuts, its 8.8-lakh-crore bond-buying program, a CRR cut, and an Iran-driven oil shock landing on top of all of it — and arguing the central bank has made a specific, nameable, conceptual mistake.

The Friedman/adaptive-expectations material itself — “inflation expectation, you know, adaptive inflation expectation is that this year’s expectation is last year’s inflation” — and the 1967 speech, and the Volcker-era inflation numbers, are the same ground Session 12 already covered in full, and this post won’t re-walk it. What follows is the part that’s new: what happens when you actually run this machinery against a real economy in real time.

The Mistake: Which R?

The whole session turns on a single definitional slip Tantri says he keeps finding among policymakers — not students, actual central bankers. The real interest rate that matters for the model isn’t nominal rate minus actual inflation. It’s nominal rate minus expected inflation. Sounds pedantic. It isn’t:

“They misunderstand this R. They think that R is nominal rate minus inflation… they misunderstand that R is nominal rate minus expected inflation. This is the biggest… it’s such a silly thing, you know, you will not even believe me unless you go and talk to them.”

Here’s how the slip played out in India, on his account. Last year, reported inflation was 1%, and the repo rate was 5.5%. By the naive formula, that’s a punishing 4.5% real rate — obviously too tight, obviously in need of a cut. RBI agreed, and didn’t stop at a cut: “they kept doing a lot of OMOs, open market operation… 8.8 lakh crores last year” in reserve-money injections, plus a CRR cut “to 3%, from 4%.” But that 1% inflation number was a one-off, driven by an unusually good monsoon pushing down food prices — not a durable drop in what people actually expect prices to do next. Expected inflation, on Tantri’s read, never fell nearly that far. Which means the real rate RBI thought it was setting and the real rate it was actually setting were two different numbers, and the gap only shows up after the fact: “R, only after the fact, now we realize that R was sitting here” — well below the neutral rate, not at it.

The mechanical consequence follows straight from the Phillips-curve apparatus this course already built: hold the real rate below neutral, and GDP runs above potential, and inflation ends up above expectations, not below. Sure enough — “it’s already started, we are at 3.25 [%]. Two-3 months ago, we were at 1% inflation” — with credit growth having “picked up to 20% or 22%” on the back of all that new money, exactly what you’d expect and exactly what he says nobody should be surprised by.

Then Iran Arrives on Top of It

That’s the setup independent of any oil shock. Now add one. An escalating Iran situation has pushed crude higher, and Tantri is precise about the mechanism: a supply shock isn’t people suddenly wanting oil more — “you don’t love gas more than before… your willingness has not changed. But on the supply side, it has changed” — which means potential GDP itself falls, and the neutral rate that was already being undershot rises further. The policy fork this creates is the same “no good choice, only bad-versus-worse” framing from Session 13, but here it’s costed out with numbers he says he’s presented to actual policymakers, met with polite disbelief: raise rates and take a slower-growth year now (his estimate: a percentage point or two off growth, “some quarters 4%… annually,” recovering “unscathed” once the shock passes) — or protect consumers at the pump and let the fiscal and monetary system absorb the shock instead.

He walks through exactly what “protecting consumers” costs mechanically, because it isn’t free just because nobody sees a price tag change:

“Your Arab sheikhs are not going to give you a discount… the government not allowing prices to going up means what? … Oil marketing companies will have to absorb these losses.”

Since the government owns those companies, the losses land on the budget one way or another — either raise taxes (politically costly, and he’s blunt that this is genuinely the best option: “at least people… will give you gali right now, and fair enough”), or borrow to cover it. He flags the second path with a specific historical precedent: P. Chidambaram’s old trick of issuing oil bonds that never showed up as fiscal deficit, going straight to the balance sheet instead — “why would he issue oil bonds? Because he would not count it as a part of fiscal deficit… this is why I think more intelligent people are more dangerous.” Borrow enough and the real rate should rise on its own through ordinary demand-for-funds mechanics — unless the central bank leans against that rise with more OMOs, in which case, he says, you get the most dangerous outcome of all: “everybody will start celebrating that we came out of this crisis unscathed” — no rate hike, no GDP hit, no visible inflation — right up until inflation expectations quietly re-anchor higher and the bill arrives with interest.

A student, Shashwat, asks the sharpest question of the Q&A: if windfall taxes get collected when crude spikes, shouldn’t that money be sitting somewhere to cushion exactly this moment? Tantri’s answer is that the mechanism only works if the money was actually saved rather than spent — a “cookie jar reserve,” in his phrase — and in India’s case it mostly wasn’t:

“If they had charged extra and created a cookie jar reserve… you have the money, but you don’t show it… Then what you’re saying is right… But, unfortorately, what they’ve done with that windfall tax — they have spent it.”

The Freebie Math

The most striking new number in the session is what state-government subsidy schemes add to this picture, worked out live at his request. Take a hypothetical ₹3,000/month household transfer scheme, scaled to Uttar Pradesh’s roughly 3-4 crore households, then scaled again to all of India (which he estimates at “6 times Uttar Pradesh”): the arithmetic lands at “something close to like 2% of GDP” in additional deficit, on top of whatever the oil shock itself costs. That’s the mechanism behind a claim he makes almost in passing but doesn’t walk back: “we have a unique situation in India where state governments will cause money printing.” States running deficits still get financed one way or another, and if the RBI is the one absorbing that pressure through OMOs rather than letting rates rise, the inflation-expectation math doesn’t care which level of government did the spending.

Try it

Reported inflation falls sharply for one year because of an unusually good monsoon, while people's actual expectations of future inflation barely move. A central bank cuts its policy rate because "the real rate looks too high" using nominal minus reported inflation. What does Tantri's model say happens next?

What You Can Now Do

The next time a central bank cuts rates because “real rates are too high,” ask which inflation number is doing the subtraction. If it’s the latest reported print rather than what people actually expect prices to do over the life of a loan or a wage contract, you have a testable hypothesis for whether the cut is genuinely neutral or quietly stimulative — and a specific, real 2026 case study (RBI’s 8.8-lakh-crore OMO program, layered under an Iran-driven oil shock) to check it against as the numbers come in over the next year or two. And when a government protects consumers from a supply shock by freezing a visible price while funding the gap through borrowing or money creation, you now know to look past the frozen number and watch two other things instead: who’s absorbing the loss on the balance sheet, and what real interest rates are doing while nobody’s rate hike is announced.

Next: /2026/06/reading-indias-balance-of-payments/ — the course leaves the real-rate diagnosis behind and turns to the external sector, reading the rupee and the balance of payments off the actual RBI data table instead of the headline exchange rate.