Big Data for Twenty-First-Century Economic Statistics

Big Data and Official Statistics†

“…While collecting the survey data needed to feed the traditional process for producing official economic statistics has become more challenging, the availability of other types of data has grown. As discussed by Bostic et al (2016), Bean (2016), Groves and Harris-Kojetin (2017), Jarmin (2019) and Abraham et al (2022), among many others, recent years have seen a proliferation of natively digital data that have enormous potential for improving economic statistics. Some of these data come from administrative records generated by federal, state and local governments that could be more widely incorporated into the production of economic statistics.…”

“…(2016), Bean (2016), Groves and Harris‐Kojetin (2017), Jarmin (2019) and Abraham et al . (2022), among many others, recent years have seen a proliferation of natively digital data that have enormous potential for improving economic statistics. Some of these data come from administrative records generated by federal, state and local governments that could be more widely incorporated into the production of economic statistics.…”

“…Private data aggregators typically view the data they have assembled as assets to be monetized rather than something to be freely shared with the statistical agencies. Nielsen has made retail scanner data available for research purposes through the Kilts Center at the University of Chicago, but the agreements under which that sharing occurs specifically exclude their use by government agencies (Abraham et al ., 2022). Even where the use of such proprietary data otherwise might be attractive, purchasing the data may be more expensive than can be justified.…”

Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity

“…Within the last decade, scanner data on purchases, credit card transaction records, and prices of various goods and services scraped from the websites of online sellers have been increasingly mainstreamed in the compilation programs of statistical agencies in advanced and emerging economies. Abraham et. al (2019) documents the progress made toward the goal-and the challenges to be overcome to realize the full potential-of using big data in the production of statistics.…”

Monetary Policy and Credit Card Spending

“…These concerns have become more acute in recent years due to declining response rates in surveys (Meyer, Mok and Sullivan, 2015). By recording actual expenditures in real-time and for a vast number of users, credit card data may thus overcome these limitations (Abraham et al, 2022). 1 Our analysis uses credit card data provided by Fable Data for Germany covering the period 2017-2021.…”