A Global Model for Forecasting Political Instability

  1. Jack A. Goldstone1,
  2. Robert H. Bates2,
  3. David L. Epstein3,
  4. Ted Robert Gurr4,
  5. Michael B. Lustik5,
  6. Monty G. Marshall6,
  7. Jay Ulfelder7,
  8. Mark Woodward8

Article first published online: 28 DEC 2009

DOI: 10.1111/j.1540-5907.2009.00426.x

Issue

American Journal of Political Science

American Journal of Political Science

Volume 54, Issue 1, pages 190–208, January 2010

Additional Information

How to Cite

Goldstone, J. A., Bates, R. H., Epstein, D. L., Gurr, T. R., Lustik, M. B., Marshall, M. G., Ulfelder, J. and Woodward, M. (2010), A Global Model for Forecasting Political Instability. American Journal of Political Science, 54: 190–208. doi: 10.1111/j.1540-5907.2009.00426.x

Author Information

  1. 1

    George Mason University

  2. 2

    Harvard University

  3. 3

    Columbia University

  4. 4

    University of Maryland

  5. 5

    Science Applications International Corporation (SAIC)

  6. 6

    George Mason University

  7. 7

    Science Applications International Corporation (SAIC)

  8. 8

    Arizona State University

*Jack A. Goldstone is Hazel Professor of Public Policy, School of Public Policy, George Mason University, 3401 Fairfax Dr. MS 3B1, Arlington, VA 22201 (jagoldsto@gmu.edu). Robert H. Bates is Eaton Professor of the Science of Government, Harvard University, 1737 Cambridge St., Cambridge, MA 02138 (robert_bates@harvard.edu). David L. Epstein is Professor of Political Science, Columbia University, New York, NY 10027 (de11@columbia.edu). Ted Robert Gurr is Distinguished University Professor Emeritus, University of Maryland, 11473 Snow Creek Ave., Las Vegas, NV 89135 (trgurr@aol.com). Michael B. Lustik is Senior Statistician, Science Applications International Corporation (SAIC), 1710 SAIC Drive, McLean, VA 22102 (Michael.B.Lustik@saic.com). Monty G. Marshall is Research Professor of Public Policy, George Mason University, 3401 Fairfax Dr. MS 3B1, Arlington, VA 22201 (mmarsha5@gmu.edu). Jay Ulfelder is Research Director for the Political Instability Task Force, Science Applications International Corporation (SAIC), 709 Kennebec Ave., Takoma Park, MD 20912 (jay_ulfelder@stanfordalumni.org). Mark Woodward is Associate Professor of Religious Studies, Center for the Study of Religion and Conflict, Arizona State University, Tempe, AZ 85287 (Mark.Woodward@asu.edu).

  1. An earlier version of this article was presented at the 2006 annual meeting of the American Political Science Association, Washington, DC. This research was conducted for the Political Instability Task Force (PITF). The PITF is funded by the Central Intelligence Agency (CIA). The views expressed herein are the authors’ alone and do not necessarily represent the views of the Task Force or the U.S. Government. Dr. Goldstone's work on this article was also supported by a Peace and Security Writing Grant from the MacArthur Foundation. We are grateful to the anonymous reviewers and editors of AJPS for their insightful comments and suggestions.

Publication History

  1. Issue published online: 28 DEC 2009
  2. Article first published online: 28 DEC 2009

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Examining onsets of political instability in countries worldwide from 1955 to 2003, we develop a model that distinguishes countries that experienced instability from those that remained stable with a two-year lead time and over 80% accuracy. Intriguingly, the model uses few variables and a simple specification. The model is accurate in forecasting the onsets of both violent civil wars and nonviolent democratic reversals, suggesting common factors in both types of change. Whereas regime type is typically measured using linear or binary indicators of democracy/autocracy derived from the 21-point Polity scale, the model uses a nonlinear five-category measure of regime type based on the Polity components. This new measure of regime type emerges as the most powerful predictor of instability onsets, leading us to conclude that political institutions, properly specified, and not economic conditions, demography, or geography, are the most important predictors of the onset of political instability.

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