On cross-lagged panel models with serially correlated errors

Lawrence S. Mayer

Research output: Contribution to journalArticlepeer-review

Abstract

Cross-lagged panel studies are studies in which two or more variables are measured for a large number of subjects at each of several points in time. The variables divide naturally into two sets, and the purpose of the analysis is to estimate and test the cross-effects between the two sets. One approach to this analysis is to treat the cross-effects as parameters in regression equations. This study contributes to this approach by extending the regression model to a multivariate model that captures the correlation among the variables and allows the errors in the model to be correlated over time.

Original languageEnglish (US)
Pages (from-to)347-357
Number of pages11
JournalJournal of Business and Economic Statistics
Volume4
Issue number3
DOIs
StatePublished - Jul 1986

Keywords

  • Autoregressive error
  • Panel analysis
  • Path analysis
  • Regression
  • Serial correlation

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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