In this paper, I examine the role of household income in determining who bribes and how much they bribe in health care in Peru and Uganda. I find that rich patients are more likely than other patients to bribe in public health care: doubling household consumption increases the bribery...

Using cross-country and Peruvian data, I show that victims of misfortune, particularly crime victims, are much more likely than non-victims to bribe public officials. Misfortune increases victims' demand for public services, raising bribery indirectly, and also increases victims' propensity to...

We provide a theoretical framework for understanding when an official angles for a bribe, when a client pays, and the payoffs to the client's decision. We test this framework using a new data set on bribery of Peruvian public officials by households. The theory predicts that bribery is more...

Using detailed Peruvian data measuring bribery, I assess which types of public official are most corrupt and why. I distinguish between the bribery rate and the size of bribes received, and seek to explain the variation in each across public institutions. The characteristics of officials'...

A free and informative press is widely agreed to be crucial to the democratic process today. But throughout much of the nineteenth century U.S. newspapers were often public relations tools funded by politicians, and newspaper independence was a rarity. The newspaper industry underwent...

The United States today, according to most studies, is among the least corrupt nations in the world. But America's past was checkered with political scandal and widespread corruption that would not seem unusual compared with the most corrupt developing nation today. We construct a "corruption...

I study data on bribes actually paid by individuals to public officials, viewing the results through a theoretical lens that considers the implications of trust networks. A bond of trust may permit an implicit quid pro quo to substitute for a bribe, which reduces corruption. Appropriate networks...