The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Serial Correlation and Serial Dependence

  • Yongmiao Hong
Reference work entry


In this article we discuss serial correlation in a linear time series regression context and serial dependence in a nonlinear time series context. We first discuss various tests for serial correlation for both estimated regression residuals and observed raw data. Particular attention is paid to the impact of parameter estimation uncertainty and conditional heteroskedasticity on the asymptotic distribution of test statistics. We discuss the drawback of serial correlation in nonlinear time series models and introduce a number of measures that can capture nonlinear serial dependence and reveal useful information about serial dependence.


ARMA models Durbin–Watson statistic Efficient market hypothesis Entropy;generalized spectral density Homoskedasticity Heteroskedasticity Kernel estimators;Lagrange multipliers Rational expectations Serial correlation Serial dependence Spectral density Statistical inference Time series analysis 

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I thank Steven Durlauf (editor) for suggesting this topic and comments on an earlier version, and Jing Liu for excellent research assistance and references. This research is supported by the Cheung Kong Scholarship of the Chinese Ministry of Education and Xiamen University. All remaining errors are solely mine.


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© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Yongmiao Hong
    • 1
  1. 1.