Government regulation of firms is associated with more negative externalities and unofficial activity across countries. I argue that this correlation mainly reflects causality going from concerns about market failures to demand for government intervention. Using trust in others as a proxy for such concerns, I show that differences in trust explain a great deal of variation in entry regulations. Then, controlling for trust in the regression of market failures on regulation, the latter is no longer associated with worse economic outcomes. The same result is confirmed when I exploit country population as an alternative source of variation in regulation.

We provide the first estimates of intergenerational income mobility using tax data for a large developing country, namely Brazil. We measure formal income from tax and payroll data, and we train machine learning models on census and survey data to predict informal income. We quantify the estimation bias resulting from income imputation and other sources of measurement error, and show that such bias remains negligible in our context. A 10 percentile increase in parental income rank is associated on average with a 5.5 percentile increase in child income rank, with considerable variation across sociodemographic groups and geographical areas.