35 For example, Albertazzi, Becker and Boucinha (2018) show evidence of the portfolio rebalancing channel from the ECB’s asset purchase programme. 30  7  All speeches are available online at www.bankofengland.co.uk/speeches  7  New, highly granular data are also coming on stream on payment, credit and banking flows. Some of these have been used to help predict, or track, movements in economic activity. They have had some success. For example, in the US a dataset of over 12 billion credit and debit card transactions over a 34 month period 36  has recently been used to analyse consumption patterns by age, firm size, metropolitan area and sector. In time, it is possible 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. This is an idea I 37  first talked about six years ago. Today, it looks closer than ever to being within our grasp. These are all areas where DAFM could contribute importantly to efforts to improve the quality and timeliness of data on the macro-economy and financial system. As is well-recognised, the scope for improvements in 38  the quality of National Accounts data is considerable. And those measurement challenges will only  become greater as we move towards an increasingly digital and service-oriented economy.
To date, they have focussed on items such as groceries and clothing. Although early days, the potential benefits in terms of increased sample sizes and granularity seem to be considerable. For example, the ONS have so far collected 7,000 price quotes per day for a group of 27  grocery items, which is larger than the current monthly collection for those items in the CPI. For GDP measurement, new sources and methods are also gaining ground. One recent study used satellite imaging to measure the amount of non-natural light emitted from different regions of the world. This has 28  been found to have a statistically significant relationship with economic activity. This approach could  potentially help in tracking activity in regions that are geographically remote, where statistical surveying techniques are poor or where mismeasurement problems are acute. A more down-to-earth example, used by the UK’s ONS and other statistical agencies, is so-called administrative data. This includes data collected by government agencies as part of their activities – for example, on tax revenue and benefit payments. In the UK, some of these data have recently become available for wider use through the government’s Open Data initiative, albeit subject to important checks. 23  Coyle (2014). Fouquet and Broadberry (2015). 25 Cavallo and Rigobon (2016). 26 Cœuré (2017). 27 See https://www.ons.gov.uk/economy/inflationandpriceindices/articles/researchindicesusingwebscrapedpricedata/august2017update 28 Henderson, Storeygard and Weil (2011).