The CBR Leximetric Datasets are the product of work carried out at the Centre for Business Research (CBR) in Cambridge, beginning in 2005 when the Centre received funding from the Economic and Social Research Council to carry out a research project on law, development and finance. Further funding from the ESRC, the European Union's FP5 and FP6 programmes, the Isaac Newton Trust, the Cambridge Political Economy Society and the International Labour Organization made it possible to expand the original datasets to their current state. As of July 2016, there are three principal datasets, coding, respectively, for labour laws in 117 countries between 1970 and 2013 (the CBR Labour Regulation Index), shareholder protection in 30 countries between 1990 and 2013 (the CBR Extended Shareholder Protection Index), and creditor protection in 30 countries between 1990 and 2013 (the CBR Extended Creditor Protection Index). The coding of legal data is carried out using a so-called leximetric coding methodology developed in the CBR and more fully explained in the codebooks which accompany each of the datasets. Taken together, the datasets provide a unique time series which enables researchers and other research users to track changes in labour, company and insolvency law over long periods of time for many countries. A distinguishing feature of these datasets is that all legal sources for the data coding are fully described in the relevant codebooks, thereby assisting transparency, external validity and replicability of results. The work of further developing the datasets on shareholder and creditor rights, so that they match the labour regulation index in terms of years and countries covered, is ongoing.

The version of the CBR-LRI (labour regulation) dataset which appears here has been superseded by an updated version. The changes were made in April 2017 and consist of (i) amendments made to the codings for certain countries (Finland, Israel and the Netherlands) in the light of feedback received after the original dataset was published; and (ii) correction of some transcription errors. For further details, please contact Simon Deakin (s.deakin@cbr.cam.ac.uk). The other two datasets have not been changed.