CORRUPTION Syndromes of Corruption

3 Participation, institutions, and syndromes
of corruption
Opportunities, constraints, and corruption
Understanding corruption in real social settings, and identifying the
variations among cases that are most important, requires careful study
of the contrasting political and economic opportunities available in
various societies, of the people and groups who seek and use (or who
are closed out of ) them, and of the institutions and norms that influence
their choices. But what are the most important contrasts? Varying
techniques (bribery, patronage) or the locations within the state seem
natural beginnings, but the prevalence of a particular technique or
venue of corruption would seem to be a response to the opportunities
and constraints present in a given situation. Categorizing corruption
by the scale of benefits involved would require much more
information than we typically have and still might not tell us very
much: does a case of a given monetary value have the same significance
where corruption is the rule compared to places where it is the exception
– or in a country where state officials have the upper hand versus
another where they are at the mercy of economic interests? Corruption
may well follow some regional patterns – African/Asian contrasts are a
prime example – but that is all the more reason to search for deeper
influences.
In this chapter I propose four corruption syndromes called ‘‘Influence
Markets,’’ ‘‘Elite Cartels,’’ ‘‘Oligarchs and Clans,’’ and ‘‘Official Moguls.’’
These syndromes, and the names suggesting their distinctive aspects,
reflect frequently encountered combinations of stronger or weaker
participation and institutions. I then employ widely used country-level
indicators of participation and institutions to sort ninety-eight countries
into corresponding groupings. Those data by themselves cannot tell us
whether corruption varies in the expected ways: that is the task of the case
studies presented in chapters 4 through 7. But they do provide a basis for
selecting cases for study that is less likely to build in expected results
beforehand.
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