Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper uses a linguistic tree, describing the genealogical relationship between all 6912 world languages, to compute measures of diversity at different levels of linguistic aggregation. By doing so, we let the data inform us on which linguistic cleavages are most relevant for a range of political economy outcomes, rather than making ad hoc choices. We find that deep cleavages, originating thousands of years ago, lead to better predictors of civil conflict and redistribution. The opposite pattern emerges when it comes to the impact of linguistic diversity on growth and public goods provision, where finer distinctions between languages matter.