Founded in 2022, the Productivity Laboratory is the TPI’s data science centre of excellence, the “engine room” for data-related activities. It is The Productivity Institute‘s scientific platform for collecting, disseminating, producing productivity data and experimenting with different analytical methods rooted in econometrics and data science.
The Productivity Lab’s primary goals are:
The TPI Productivity Lab’s portals structures the datasets and additional content by their spatial dimension, providing information at the:
Within these spatial dimensions, it further subdivides the content along three economic dimensions:
The TPI Productivity Lab is the main outlet for data sets that are funded and produced by The Productivity Institute. These datasets are hosted on the Figshare platform- TPI Productivity Lab’s subgroup. Figshare is an official data repository where users can make all of their research outputs available in a citable, shareable, and discoverable manner. Figshare supports and provides several important features for hosting research data:
The productivity lab has recently constituted the TPI Productivity Lab Expert group, chaired by Professor Rebecca Riley (King’s College London) and composed of members of data-related institutions such as ONS and OECD. The lab’s expert group will be requested to provide advice on critical data-related topics linked with the lab’s programme of activities as well as evaluate and assess the quality of its activities.
The TPI Productivity Lab is currently engaged in activities with ESCoE, ONS, The Conference Board, EUKLEMS-Intanprod-LUISS, CompNet, OECD, Groningen Growth and Development Centre (CGDC), among other data-related partners.
At the lab, we are constantly engaging with other institutions to bring data insights, datasets, and data-related tools! The lab will soon start engagement data-related activities including workshops and a fellowship – studentship programme. Stay tuned!
For questions regarding the Productivity lab’s blogs, data, or requests for potential collaboration, including hosting or disseminating any productivity data-related opportunities, please send us an e-mail.