In an attempt to determine the causes and consequences of corruption, academics have focused lately on cross-country analyses. These require assessments of the extent of corruption in various countries. Such assessments are sometimes compiled by agencies to determine country risks, and the data gathered are sold to investors. Other sources are surveys of elite businesspeople or the general public. While perceptions should never be confused with reality, the given consensus provides some confidence that the perceptions gathered are informative on actual levels of corruption. Most prominent in recent years has been the TI CPI.

Objective versus subjective data

Instead of using perceptions data, Goel and Nelson (1998), Fisman and Gatti (2002) and Glaeser and Saks (2006) employ objective data: the number of public officials convicted for abuse of public office in various states of the United States. They assume that high conviction rates are an indicator of actual high levels of corruption. Certainly, conviction rates may not well depict levels of corruption but rather the quality of the judiciary. But Glaeser and Saks (2006) defend the data on the grounds that they refer to central government prosecutor's charges and convictions, not those by the local judiciary. Glaeser and Saks (2006) report that conviction rates decrease with income and education. Goel and Nelson (1998) significantly relate conviction rates to the real per capita total expenditures of the local government, arguing that state intervention and public spending give rise to rent-seeking activities and thereby corruption.