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A Linear Poisson Autoregressive Model: The Poisson AR(p) Model

  • Patrick T. Brandt (a1) and John T. Williams (a1)

Time series of event counts are common in political science and other social science applications. Presently, there are few satisfactory methods for identifying the dynamics in such data and accounting for the dynamic processes in event counts regression. We address this issue by building on earlier work for persistent event counts in the Poisson exponentially weighted moving-average model (PEWMA) of Brandt et al. (American Journal of Political Science 44(4):823–843, 2000). We develop an alternative model for stationary mean reverting data, the Poisson autoregressive model of order p, or PAR(p) model. Issues of identification and model selection are also considered. We then evaluate the properties of this model and present both Monte Carlo evidence and applications to illustrate.

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Nathaniel Beck . 1991. “Comparing Dynamic Specifications: The Case of Presidential Approval.” Political Analysis 3: 5187.

Janet M. Box-Steffensmeier , and Bradford S. Jones 1997. “Time Is of the Essence: Event History Models in Political Science.” American Journal of Political Science 41(4): 14141461.

Patrick T. Brandt , John T. Williams , Benjamin O. Fordham , and Brian Pollins . 2000. “Dynamic Models for Persistent Event Count Time Series.” American Journal of Political Science 44(4): 823843.

Bryan Brophy-Baermann , and John A. C. Conybeare 1994. “Retaliating Against Terrorism: Rational Expectations and the Optimality of Rule Versus Discretion.” American Journal of Political Science 38(1): 196210.

A. Colin Cameron , and Pravin K. Trivedi 1998. Regression Analysis of Count Data. Cambridge: Cambridge University Press.

Gary Grunwald , Kais Hamza , and Rob Hyndman . 1997a. “Some Properties and Generalizations of Non-negative Bayesian Time Series Models.” Journal of the Royal Statistical Society, Series B 59(3): 615626.

D. F. Hendry , A. R. Pagan , and J. D. Sargan 1984. “Dynamic Specification.” In Handbook of Econometrics, Vols. 2 and 3, ed. Z. Griliches and M. D. Intriligartor Amsterdam: North-Holland.

Gary King . 1988. “Statistical Models for Political Science Event Counts: Bias in Conventional Procedures and Evidence for the Exponential Poisson Regression Model.” American Journal of Political Science 32(3): 838863.

Gary King . 1989. “Variance Specification in Event Count Models: From a Restrictive Assumptions to a Generalized Estimator.” American Journal of Political Science 33(3): 762784.

David E. Lewis , and James Michael Strine . 1996. “What Time Is It? The Use of Power in Four Different Types of Presidential Time.” Journal of Politics 58(3): 682706.

Edward D. Mansfield 1992. “The Concentration of Capabilities and the Onset of War.” Journal of Conflict Resolution 36(2): 324.

Sean P. O’Brien 1996. “Foreign Policy Crises and the Resort to Terrorism.” Journal of Conflict Resolution 40(2): 320335.

Brian Pollins . 1996. “Global Political Order, Economic Change, and Armed Conflict: Coevolving Systems and the Use of Force.” American Political Science Review 90(1): 103117.

Lois W. Sayrs 1992. “The Effect of Provocation on Foreign Policy Response: A Test of the Matching Hypothesis.” International Interactions 18(2): 85100.

Paul D. Senese 1997. “Costs and Demands: International Sources of Dispute Challanges and reciprocation.” Journal of Conflict Resolution 41(3): 407427.

James F. Spriggs , and Paul J. Wahlbeck 1995. “Calling It Quits: Strategic Retirement on the Federal Courts of Appeals, 1893–1991.” Political Research Quarterly 48(3): 573597.

Halbert White . 1994. Estimation, Inference and Specification Analysis. Cambridge: Cambridge University Press.

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Political Analysis
  • ISSN: 1047-1987
  • EISSN: 1476-4989
  • URL: /core/journals/political-analysis
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