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Equation Balance and Dynamic Political Modeling

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  • Lebo, Matthew J.
  • Grant, Taylor

Abstract

The papers in this symposium agree on several points. In this article, we sort through some remaining areas of disagreement and discuss some of the practical issues of time series modeling we think deserve further explanation. In particular, we have five points: (1) clarifying our stance on the general error correction model in light of the comments in this issue; (2) clarifying equation balance and discussing how bounded series affects our thinking about stationarity, balance, and modeling choices; (3) answering lingering questions about our Monte Carlo simulations and exploring potential problems in the inferences drawn from long-run multipliers; (4) reviewing and defending fractional integration methods in light of the questions raised in this symposium and elsewhere; and (5) providing a short practical guide to estimating a multivariate autoregressive fractionally integrated moving average model with or without an error correction term.

Suggested Citation

  • Lebo, Matthew J. & Grant, Taylor, 2016. "Equation Balance and Dynamic Political Modeling," Political Analysis, Cambridge University Press, vol. 24(1), pages 69-82, January.
    • Handle: RePEc:cup:polals:v:24:y:2016:i:1:p:69-82_7
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    Cited by:

    1. Santiago López-Cariboni & Xun Cao, 2019. "When do authoritarian rulers educate: Trade competition and human capital investment in Non-Democracies," The Review of International Organizations, Springer, vol. 14(3), pages 367-405, September.
    2. Bakker, Vincent & Van Vliet, Olaf, 2019. "Social Investment, Employment Outcomes and Policy and Institutional Complementarities: A Comparative Analysis across 26 OECD countries," MPRA Paper 96140, University Library of Munich, Germany.

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