@workingpaper {645191,
	title = {A Rosetta Stone for Human Capital},
	year = {Working Paper},
	abstract = {Understanding the causes and consequences of international differences in human capital is a central concern of economics. But how can we accurately measure the global distribution of skills when people in different countries take different tests? We develop a new methodology to non-parametrically link scores from distinct populations. By administering an exam combining items from different assessments to 2,300 primary students in India, we estimate conversion functions among four of the world{\textquoteright}s largest standardized tests spanning 80 countries. Armed with this learning {\textquotedblleft}Rosetta Stone,{\textquotedblright} we revisit various well-known results, showing, inter alia, that learning differences between most- and least-developed countries are larger than existing estimates suggest. Applying our translations to microdata, we match pupils{\textquoteright} socio-economic status to moments of the global income distribution and document several novel facts: (i) students with the same household income score significantly higher if they live in richer countries; (ii) the income-test score gradient is steeper in countries with greater income inequality; (iii) girls read better than boys at all incomes but only outperform them in mathematics at the lowest deciles of the global income distribution; and (iv) the test-score gap between public and private schools increases with inequality, partially due to a rise in socio-economic sorting across school types.},
	url = {https://www.cgdev.org/publication/rosetta-stone-human-capital},
	author = {Dev Patel and Justin Sandefur}
}
