Economic indicators are statistics that measure an economic activity or phenomenon.
High quality economic indicators are hugely important for policymakers, researchers and the general public for a number of reasons:
- to help policymakers assess the state of the economy and formulate policy accordingly, as well as assess the impact of past interventions
- inform businesses and the public while enabling them to make well-informed economic decisions and to hold government to account
- to allow researchers to conduct empirical research and gain a better understanding of the economy and society
The gold standard for UK economic indicators are National Statistics that have been assessed by the Office for Statistics Regulation. It has full compliance with a Code of Practice for Official Statistics that ensures they are of public value, high quality and can be trusted.
The 2016 Bean Report found public trust in the independence of economic indicators, produced by the Government Statistical Service, was encouragingly high. However, it called for improvements to quality and timeliness of statistics, as well as further novel approaches.
There is also interest across Whitehall in alternative measures of economic activity, for example capturing the value of the digital economy.
This interest, in combination with recent advances in technology, analytical methods and data availability, has led to the development of a range of experimental economic indicators across academia and statistical agencies.
Experimental economic indicators
As part of a wider stream of work on economic indicators, the Open Innovation Team has reviewed a wide range of academic literature and the work of statistical agencies around the world.
We highlight two important ways in which an economic indicator can be experimental:
- A novel or experimental data source not currently used in official statistics for that purpose.
- An experimental approach – attempting to measure something not covered by existing statistics.
We've classified experimental work according to this framework. For example, Office for National Statistics' work incorporating web-scraped prices into their measures of CPI uses an experimental data source to improve official statistics. So this would fit into the top right quadrant.
Research attempting to produce short-term forecasts or more detailed measures using official statistics uses traditional data sources, but an experimental approach - which attempts to measure something not covered by current statistics - would fit into the bottom left quadrant.
Several factors need to be considered when assessing the value of data sources used for indicators. Social media data may be easily available, but its relevance to economic variables of interest is less clear. Electronic payments data appears to be relevant for key variables, such as consumer spending, but is largely privately held.
In assessing whether a novel approach is worth pursuing, the potential use, robustness and accuracy of the indicator need to be considered.
The ultimate aim in developing an experimental economic indicator will be to incorporate it into the set of National Statistics, so the Code of Practice may be the ultimate judge.
The Open Innovation Team is identifying opportunities for increasing academic engagement and experimental work on economic indicators across government.