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α: calibrated so average coauthorship-adjusted count equals average raw count
Abstract We propose a new method to approximate income distribution dynamics at the micro level using only macro data on aggregate moments of the income distribution. Under the assumption that individual incomes follow a lognormal autoregressive process, we show that the evolution of the mean and standard deviation of log income across individuals provides sufficient information to bound the degree of mobility. We estimate mobility bounds for 46 countries, using time series data on aggregate moments of the income distribution available in the World Inequality Database and the World Bank’s PovcalNet database. This new data allows us to study the correlates of mobility, and to document churning in the top and bottom of the income distribution, in a much larger set of countries than was previously possible.