Andy Haldane, chief economist of Bank of England, reacts during the launch of the central bank's econoME education programme in the City of London, U.K., on Friday, April 27, 2018. Money markets have slashed bets on the Bank of England raising borrowing costs when it meets in two weeks, with the odds for an increase collapsing to 20 percent from above 50 percent on Thursday. Photographer: Simon Dawson/Bloomberg
Andy Haldame backs increased use of big data © Simon Dawson/Bloomberg

The goal of mapping economic activity in real time, just as we do for weather or traffic, is “closer than ever to being within our grasp”, according to Andy Haldane, the Bank of England’s chief economist.

In recent years, “data has become the new oil . . . and data companies have become the new oil giants”, Mr Haldane told an audience at King’s Business School earlier this month and released on Monday.

But economics and finance have been “rather reticent about fully embracing this oil-rush”, partly because economists have tended to prefer a deductive approach that puts theory ahead of measurement.

This needs to change, he said, because relying too much on either theory or real-world data in isolation can lead to serious mistakes in policymaking — as was seen when the global financial crisis exposed the “empirical fragility” of macroeconomic models.

Parts of the private sector and academia have been far swifter to exploit the vast troves of ever-accumulating data now available — 90 per cent of which has been created in the last two years alone.

Massachusetts Institute of Technology’s “Billion Prices Project”, name-checked in Mr Haldane’s speech, now collects enough data from online retailers for its commercial arm to provide daily inflation updates for 22 economies.

The Alan Turing Institute — the UK’s new national institute for data science — runs a programme, with funding from HSBC, which aims to use new data to measure economic activity faster and more precisely than was previously possible.

National statisticians are taking tentative steps in the same direction. The UK’s Office for National Statistics — which has faced heavy criticism over the quality of its data in recent years — is experimenting with “web-scraping” to collect price quotes for food and groceries, for example, and making use of VAT data from small businesses to improve its output-based estimates of gross domestic product.

In both cases, the increased sample size and granularity could bring considerable benefits on top of existing surveys, Mr Haldane said.

The BoE itself is trying to make better use of financial data — for example, by using administrative data on owner-occupied mortgages to better understand pricing decisions in the UK housing market.

Mr Haldane sees scope to go further with the new data coming on stream on payment, credit and banking flows. “Almost all economic activity leaves a financial footprint,” he said. “In time, it is possible that these sorts of data could help to create a real-time map of financial and activity flows across the economy, in much the same way as is already done for flows of traffic or information or weather. Once mapped, there would then be scope to model and, through policy, modify these flows.”

New data sources and techniques could also help policymakers think about human decision-making — which rarely conforms with the rational process assumed in many economic models. Data on music downloads from Spotify, used as an indicator of sentiment, has recently been shown to do at least as well as a standard consumer confidence survey in tracking consumer spending.

“Why stop at music?” Mr Haldane asked. He saw potential to create a gaming environment “to explore behaviour in a virtual economy where players can spend or save, and one could test their reactions to monetary and regulatory policy intervention”.

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