A Continuous-Time, Latent-Variable Model of Time Series Data. (2015)

• Record Type: Journal Article
• Authors: Tahk, Alexander M.
• Is Part Of: Political analysis. Volume 23:Number 2(2015:Summer)
• Page Start: 278
• Page End: 298
• Publication Date: 2015
• Subjects: Political science -- Methodology -- Periodicals; Electronic journals; 320.011
• DOI: 10.1093/pan/mpu020
• Languages: English
• ISSNs: 1047-1987

Abstract

Abstract : Many types of time series data in political science, including polling data and events data, exhibit important features'such as irregular spacing, noninstantaneous observation, overlapping observation times, and sampling or other measurement error'that are ignored in most statistical analyses because of model limitations. Ignoring these properties can lead not only to biased coefficients but also to incorrect inference about the direction of causality. This article develops a continuous-time model to overcome these limitations. This new model treats observations as noisy samples collected over an interval of time and can be viewed as a generalization of the vector autoregressive model. Monte Carlo simulations and two empirical examples demonstrate the importance of modeling these features of the data.