Time-Series Cross-Section Methods

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This article outlines the literature on time-series cross-sectional (TSCS) methods. First, it addresses time-series properties including issues of nonstationarity. It moves to cross-sectional issues including heteroskedasticity and spatial autocorrelation. The ways that TSCS methods deal with heterogeneous units through fixed effects and random coefficient models are shown. In addition, a discussion of binary variables and their relationship to event history models is provided. The best way to think about modeling single time series is to think about modeling the time-series component of TSCS data. On the cross-sectional side, the best approach is one based on thinking about cross-sectional issues like a spatial econometrician. In general, the critical insight is that TSCS and binary TSCS data present a series of interesting issues that must be carefully considered, and not a standard set of nuisances that can be dealt with by a command in some statistical package.

Original languageEnglish (US)
Title of host publicationThe Oxford Handbook of Political Methodology
PublisherOxford University Press
ISBN (Electronic)9780191577307
ISBN (Print)9780199286546
DOIs
StatePublished - Aug 21 2008

Keywords

  • Binary variables
  • Fixed effects
  • Heterogeneous units
  • Heteroskedasticity
  • Nonstationarity
  • Random coefficient models
  • Spatial autocorrelation
  • Time-series cross-sectional methods

ASJC Scopus subject areas

  • Social Sciences(all)

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  • Cite this

    Beck, N. (2008). Time-Series Cross-Section Methods. In The Oxford Handbook of Political Methodology Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199286546.003.0020