Category: Data Analytics and AI
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This post estimates potential labor market transition pathways based on the similarity of skills, abilities and knowledge required by occupations. The approach broadly follows Bratanova et al. (2026). Like their research, the considered transition pathways are for workers currently employed as truck drivers. Unlike their approach, we've used a more recent version of the O*NET database and a different SOC-to-ANZSCO crosswalk. Although the point wasn't to precisely replicate their results, our approach largely did, with differences in similarity scores likely stemming from our different mapping of the SOC to the ANZSCO rather than from the method itself.
There's no official crosswalk between the ONET's occupational taxonomy and ANZSCO, which is awkward, because Australian researchers use ONET data all the time. This post builds one, explains why you should be suspicious of relying on it and then suggests a better methodology is probably what was applied by the European Commission.
The first post established that the WGI and WJP rule of law measures agree on how they rank countries. This follow-up tests the stricter question of whether the WGI can predict the WJP’s levels, rather than just the relative ranking / relative position of countries. It can: forecasting errors appear to be minimal and don’t vary significantly over time.
This post examines whether the Worldwide Governance Indicators' (WGI) rule of law measure provides a reasonable proxy for the World Justice Project's (WJP) Rule of Law Index, such as when analysis might benefit from the WGI's availability for more countries over a longer period. Results suggest the two measures broadly agree with one another when making cross-country comparisons, but care is warranted for country-level estimates where it's likely to be more difficult to differentiate measurement noise from genuine changes in the quality of institutions.