State failure project

From Pardee Wiki
Jump to navigation Jump to search

Center for International Development and Conflict Management (CIDCM):  State Failure Project

State failure datasets provide comparative information on cases of total and partial state failure during 1955 to 2001 in independent countries populated by more than half million people.  The project was initiated by Ted Gurr of University of Maryland in 1994 and lists state-failure events, indicating the starting and ending dates for all serious cases of four different kinds of internal political crisis—revolutionary wars, ethnic wars, adverse regime changes, and genocides.

The list of state failure events has been compiled from multiple sources by researchers at the Center for International Development and Conflict Management (CIDCM), University of Maryland, and is available at  http://www.cidcm.umd.edu/publications/publication.asp?pubType=paper&id=9 (link to State Failure Task Force Report: Phase III Findings Aug 2003).  The project has kindly made the data available.

In the IFs system, data series are available on each of the four types of state failure and also on consolidated events across one or more types of failure.  Series have been included for initial events, for initial and continuing events, and for event magnitude.  In addition, data series have been added for analytic purposes that, for internal war (revolutionary wars, ethnic wars, and genocides) and for instability (adverse regime changes), show average probabilities over all years, the last 30 years, last 20 years, and last 10 years.

Diehl, Paul:  Contiguity Data

Professor Paul Diehl, professor at the University of Michigan, has built a database that represents the degree of contiguity or distance between pairs of countries.  Because of the close relationship between distance separating countries and the extent of cooperation and conflict between them,  This measure is very useful in the international political formulations of IFs.  Paul Diehl was kind enough to provide access to his database.

Because of its dyadic characteristic, these data are not available for analysis with the statistical tools of IFs.  They are used by the preprocessor and a variable in IFs carries information on contiguity for the model. See http://www.correlatesofwar.org/COW2%20Data/DirectContiguity/DCV3desc.htm.