1/n
Having looked a fair bit at India's electricity demand trends recently, I thought I would do the same for petroleum products today.

What I found surprised me.

Thread warning.
2/n
Firstly, unlike electricity demand, 2019 doesn't seem to be a particularly 'bad' year for petroleum product demand. 'Bad' in the sense of concern about Indian economic growth. For climate change, of course every increase in ff consumption is bad.
3/n
Bottom line is that India's total petroleum product demand is up 3.1% against the same period last year (Jan-Nov).

As seen 👇 India's oil product demand tanked in 2018, not 2019.

So probably what we are seeing this year is as much a low base effect as actual fast growth.
3/n
But there is something odd about the graph 👆. India's oil product demand growth rates haves been on a sharply downwards trajectory since 2015.
4/n

At the same time, global oil prices collapsed and India's real effective exchange rate appreciated (i.e. increased real international purchasing power of the rupee, hence effectively further lowering the cost of imported oil).
👇
5/n
So why didn't India's oil price demand increase more in the face of a 50% collapse in oil prices and 20% increase in the REER?

Short answer is: the government taxed away the benefit.

By increasing fuel taxes, nominal prices for fuels fell only marginally.
6/n
This was a massive windfall for the government exchequer and significantly constrained the increase in Indian fuel consumption, even as oil prices fell and the rupee gained in international purchasing power.

This raises the Q: by how much did it hold back fuel demand?
7/n
To address this question, I built a little econometric model that takes oil price, GDP, and real effective exchange rate, and trained it on quarterly data from 2000-14.
The graph shows the predicted level of oil demand versus actual oil demand from 2000-19.
8/n
The figure 👇 zooms in on the out of sample years 2014-19.
Here the model - correctly - forecasts higher than actual oil product consumption in the years 2014-15, by as much as 3% in 2015.
In 2016, actual is higher than forecast.
9/n
In 2016, nominal fuel prices fell as reached their lowest level, and - I guess - the government did not fully absorb this in tax increases.
The model overestimates fuel consumption in 2017. This was a year of both strong currency appreciation and benign oil prices.
10/n
That the model over-forecasts oil demand suggests something else is as play.
My guess is that tax rates on fuels were steady, and may be that the GDP numbers, with 2017 being shortly after demon and GST, don't actually reflect the ground reality fully.
11/n
The model is close to actual on 2018, when fuel consumption growth fell. In 2018, the currency depreciated and oil prices hiked, meanwhile the government couldn't lower fuel taxes because of fiscal constraints.
12/n
So my takeaways:
1. Unlike elec, fuel consumption is holding up in 2019.
2. This is likely due to the low base effect of 2018, as well as more benign oil price and rupee conditions.
3. The real story how much fiscal policy constrained oil demand growth 2014-17.
13/n
Given what we now know about the Indian economy it can be asked whether it was the 'right' choice to prioritise fiscal consolidation over passing some of the windfall to consumers.
Had we known how bad the NPA situation was, maybe prioritising growth was a better option.

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More from @ThomasASpencer

Dec 28, 2021
1/10
Back in India, back reading about India.
It's time for another 10 tweet review.

Book: Whole Numbers and Half Truths: What Data Can and Cannot Tell Us About Modern India

Author: Rukmini S. @Rukmini
2/10
Firstly, this book gets an A-plus for the pun (visual and titular) that you get right from the cover.

@Rukmini is a data journalist from Chennai, one of the field's Indian pioneers and a leading voice in interpreting India's covid experience.
3/10
Her book brings together four key characteristics of a good data journalist.
First, she has a sensitivity to the importance of the process of data production. A fascinating description of how all is not what it seems in data on sexual assualt is a case in point.
Read 10 tweets
Feb 23, 2021
1/n Today we published a model-based assessment of the grid integration costs of VRE.
Note: we only look at profile and balancing costs, not network costs.
Here I summarize the results in 6 easy tweets.
2/n
In all scenarios we study, a short-term 'optimal' level of VRE is substantially higher than current levels, in the order of 40% of total generation.
This is robust to assumptions on demand, storage cost, cost of capital, retirement of end of life assets, etc.
3/n
The substitution of expensive energy with cheap VRE allows total system costs to decline as we approach 'optimal VRE', even as total system-wide fixed costs go up.
Basic point: cheap energy + expensive capacity is a winning combination for substantially higher VRE.
Read 8 tweets
Jan 4, 2021
1/n
We ended 2020 with the news that India's power demand cross 180 GW for the first time. Unusually, this occurred in December, when power demand usually peaks is in summer?

What is going on here? Is it sign of the economic recovery?

Short thread.
2/n
Firstly, as I have been repeating, we need to look carefully at both base effect and time period when looking at demand growth.

Monthly demand smooths out daily fluctuations, and comparing 2020 against both 2019 and 2018 shows the importance of the base effect. 👇 Image
3/n
Compared against 2018, 2020 monthly demand has registered only a few months of growth since the lockdown effectively ended in June.

Because of the collapse in demand in the second half of 2019, the picture looks more optimistic if we compare against 2019 (low base effect)
Read 9 tweets
Dec 21, 2020
1/n
Last week TERI released its flagship report on the prospects for H2 in India.

The full report is here. bit.ly/3poYA2n

At 140 pages, I can't summarize the whole thing in a single thread, but I can do a series of threads.

Today's: H2 in the Indian power sector.
2/n
We do a bottom up assessment to 2050 of power demand across all sectors, including direct and indirect electrification (for electrolytic H2 production).

In the low carbon scenario, power demand reaches as much as 6200 TWh by 2050, with almost 1000 TWh of that for H2. 👇
3/n
This would consume a very substantial chunk of India's maximum estimated technical potential for onshore wind and solar PV. 👇
The required rate of supply growth and land footprint may be challenging!

This reinforces the message: direct electrification wherever possible.
Read 12 tweets
Sep 30, 2020
1/n
In today's thread, I want to take a look at India's NDC target of reducing the GHG intensity of GDP by 33-35% by 2030, compared to 2005.

I argue that this target is essentially BAU, because India's GHG intensity of GDP is declining as a natural part of development.

Thread
2/n
If we take a long run view of the GHG intensity of India's economy since 1947, it can be seen that GHG intensity peaked in about 1985 and has been declining ever since.

Why is this?
3/n
Firstly, this pattern is common to developing countries across the long-run development trajectory:
- China
- South Korea
- Thailand
- Japan

All experienced this kind of peak and decline structure (Japan and Thailand somewhat early than I graph here).

Why is this?
Read 15 tweets
Sep 23, 2020
1/n
Yesterday Xi Jinping announced that China would peak its emissions and work towards net zero emissions by 2060.

What does this mean for India?

A short thread on why India is fundamentally different from China, and how it could respond in its climate diplomacy.
2/n
India is, simply put, a much poorer country than China. Its GDP at PPP is 57% below that of China. But I think this actually understates how far India is behind China.

Another way of looking: India's final energy consumption per capita is 70% below that of China.
3/n
Even at PPP, China's final energy intensity of GDP is 30% higher than India's.

Why is this? Essentially, it boils down to economic structure 👇. China's industry share in GDP is much higher than India, and China's industry sector is more energy intensive.
Read 15 tweets

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