“First Day First Show”: Did Odd-Even work? and how Media played its part

Call it a novel idea, call it “Tughlaq-esque”, Delhi’s Odd-Even plan caught the eye of many in India and most on social media. One of the reasons for this could be our Delhi based media’s infatuation with the Delhi state Government which often leads it to conflate stories which are important to Delhi, with stories which matter for India as a whole. Add to that Arvind Kejriwal’s penchant for making a media spectacle out of anything he does (based on advice from his Guru Rajdeep Sardesai) and you have a sure shot prime-time debate topic.

So did this Odd-Even experiment work based on Day 1 results? Is it even fair to judge something based on the results of the 1st day? Lets get to the 2nd question later. First see how our media reported it:

As many on Twitter pointed out, “First Day, First Show” was the preferred phrase for what could have been synchronized tweeting by some of our top journalists, just as the experiment began.

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The reports became fuzzier as the day went by, with some journalists like Vishnu Som from NDTV determined to prove Odd-Even worked against all “odds”. This even while his own channel NDTV was simultaneously running a story which said Air quality had shown no marked change and was still poor. Amusingly, Som’s claims and NDTV’s reports, both claimed to be based on the same SAFAR report. A report in India-Today cited multiple studies and data sources showing that Odd-Even plan may not have worked on Day 1.

Times of India too was running a similar story saying air quality had not really improved. But, come morning, Times of India’s data had changed drastically and splashed across its print edition was this news that claimed Odd-Even worked. To back this claim, Times of India chose to compare pollution levels on 31st December 2015 with 1st January 2016:

The basic fallacy among all the reports above, whether positive or negative was their premature jumping to conclusions, based on data of only 1 day. Even this day is a very bad sample to be taken to judge the efficacy of the plan. Consider this: 1st January is a holiday for a large number of establishments by virtue of being the 1st day of the year. It marked the start of a long weekend owing to which it is natural to expect a large number of city dwellers to head out of the city. Can an outlier of a day be used to judge an experiment? This is something which is taught at the most basic level of statistical sampling. Even worse, can just 1 day be taken into account to make any sort of claim?

The next big brain-fade is comparing the data of 1st January, with the data on 31st December, like Times of India did. It is unbelievably stupid to compare a holiday with a day which sees traffic snarls. But then logic and common sense have never been the forte of Times of India.

A larger point here is, is it even fair to expect any change in 1 day? Air pollution is not something which can be wished away in a day. It takes sustained efforts over a long period to show credible results. And Delhi is not an insulated pocket which is not affected by surrounding areas. While areas in the NCR region like Noida continue with their usual pollution levels, is it fair to expect Delhi to remain completely unaffected? In the world of quick-fixes and desire for even quicker results such nuances and realities are all but lost.

Coming to the actual Odd-Even plan as it stands, can any finding from this 15 day period be credible? Schools have been asked to shut down, thus artificially reducing traffic which would have been there on any normal day. The results of an experiment are credible only when all other things are kept constant (ceteris paribus) and only the change, here the plan of odd-even cars, is implemented.

Add to this the number of exemptions given, the plan loses most of its teeth. A report suggests after all exemptions are taken car of, the odd-even plan would affect only 6% of of cars. For all the brouhaha if a meagre 6% is what the best case scenario is, then the plan needs serious rethinking. Besides the sheer number, even the type of exemptions are questionable. Take for example the exemption given to two-wheelers. Multiple studies show motorcycles pollute way more, from 10 to 16 times worse than cars. And we have elected legislators of AAP itself “setting an example” by riding motorcycles to work:

At this stage the questions are many. Can day 1 data be used to claim a victory or defeat? With inbuilt aberrations in test conditions, will even 15-day data be helpful? Data aside, are the technicalities in the plan defeating the very purpose of the plan?

Some people have also begun branding anyone opposed to the Odd-Even plan as Anti-Delhiite or Pro-Pollution. A comparison is made to the Swacch Bharat Abhiyaan run by the Central Government and how the opposers of that move were  branded anti-Nationals. Here, a fundamental flaw in comparison arises since the 2 are frankly completely different.

Swacch Bharat is an aim, a mission, a target. The means to achieve this target are measures like photo-ops by celebrities, nominations of influencers to take up the task, awareness about cleanliness, Swacch Bharat Cess, focus on building toilets, launch of Air Quality Index etc. Similarly, in Delhi, Clean Air is the mission and Odd-Even plan is just a means of achieving this plan. In case of Swacch Bharat, we saw numerous people trashing the measures such as photo-ops etc. Similarly, this time many people are voicing concerns over the Odd-Even plan because they feel it is not practical. Surely everybody wants a cleaner India and cleaner air, the disagreement is only on the methods.

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Having said all of the above, the AAP Government deserves kudos for deciding to actually do something, and backing it fully. Sure, this action was prompted by a rap from the Supreme Court but the Government did act. The common refrain of “at least he is doing something” holds good here because we really haven’t seen any Government in India take up the cause of air pollution with such aggression, however foolhardy one might consider the actual methods.


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