Time-Series Cross-Section Methods

Research output: Chapter in Book/Report/Conference proceedingChapter


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
StatePublished - Aug 21 2008


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

ASJC Scopus subject areas

  • General Social Sciences


Dive into the research topics of 'Time-Series Cross-Section Methods'. Together they form a unique fingerprint.

Cite this