The NY Times has published a neat article about NYU’s new urban “Big Data” center. Â The gist of the article is that urban quality of life can be improved by the quants crunching the data on things such as the spatial and temporal distribution of 311 Noise calls in NYC.
“The initiative at N.Y.U. is part of a broader trend: the global drive to apply modern sensor, computing and data-sifting technologies to urban environments, in what has become known as â€œsmart cityâ€ technology. The goals are big gains in efficiency and quality of life by using digital technology to better manage traffic and curb the consumption of water and electricity, for example. By some estimates, water and electricity use can be cut by 30 to 50 percent over the course of a decade.”
This last sentence is false. Â “Big data” is a necessary but not a sufficient condition for conservation and better use of urban scarce resources. Â I am a 100% fan of having better outcome variables (i.e Y from basic statistics) such as local air pollution, household energy consumption, and noise levels at a given street on a given day but such information alone does not establish cause and effect. Â Big data needs to be supplemented with field experiments to have random interventions such as introducing time of day electricity pricing to raise the price of a KWh at peak use times to protect the grid from overload. Â Big Data allows for better measurement but the social scientists can only establish cause and effect if specific interventions are known to have been implemented (i.e a ban on traffic near the UN when Castro is in town).
I have been working on this issue in my work using electric utility data by household/month. Â We can only make progress establishing cause and effect if we know something about the households. Â Â In the typical “Big Data” electric utility data set, the only thing the researcher knows is the zip code where the household lives and the year and month when the electricy consumption took place. Â Is such “big data” (there are millions of these records) sufficient to establish how to increase conservation? Â No!!
To achieve 30 to 50% reductions in water and electricity will require introducing serious economic incentives for conservation. Â The article does not mention the word incentive anywhere in the article, instead it focuses on sociological nudges. Â That’s a good start but such social “keeping up with the Jones” incentives are not sufficient to achieve the aggressive 30% reduction. Â Engineers need to play nice with the economists and vice-versa. Â There are gains to trade here!
4 thoughts on “Big Data and Field Experiments: The Case of NYU’s Center for Urban Science and Progress”
“This last sentence is false. â€Big dataâ€ is a necessary but not a sufficient condition for conservation and better use of urban scarce resources.”
Your first sentence is true. Your second sentence is as false as the one you are criticizing. There are many other ways to conserve energy and make better use of scarce resources. For example, increasing taxes on energy consumption, giving incentives for installing energy-saving appliances and insulation, new rules that outlaw certain substandard devices and construction methods, and many other ways. While big data can help, it is not necessary for most of these things to work (as other countries have shown over the last few decades).
In fact, this is much more true for the US than for other advanced countries, since in the US there is still a lot of low-hanging fruit – a lot of the windows that are being installed in new construction, heating systems that are in operation, etc, would be illegal in other countries that have already taken steps to reduce energy. Friends visiting from Europe are always shocked by what they see in New York apartments – overheated apartments with the only way to control temperature being opening the windows, or single-pane windows when in places in Europe with comparable climate, triple pane is pretty much becoming the norm. It is simply outrageous what is still legal.
Anyway, I understand the lure of big data in this context. It promises improvements without much pain, just by the magic of technology, without any need to spend political capital on an issue that most Americans just don’t give a flying **** about. And if it doesn’t work, we can then complain about how it is sooo difficult to save energy in the US. But let’s face it, energy consumption in the US is higher than in many other places not just because of different settlement patterns, but because there is absolutely no will to actually address the problem. And technology will not magically solve the problem for us, even if you widen the academic playing field by inviting economists to join in. It is about the politics, not the science. Waiting for the science fairy just helps kicking the can down the road for another decade.
I have been working on this issue in my work using electric utility data by household/month.
We’ve established in Colo for water that this only works sometimes. It works better with tiered pricing and feedback, but only sometimes, and more often with the rich.
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