LAD asymptotics under conditional heteroskedasticity with possibly infinite error densities

Jin Seo Cho, Chirok Han, Peter C.B. Phillips

Research output: Contribution to journalArticle

3 Citations (Scopus)


Least absolute deviations (LAD) estimation of linear time series models is considered under conditional heteroskedasticity and serial correlation. The limit theory of the LAD estimator is obtained without assuming the finite density condition for the errors that is required in standard LAD asymptotics. The results are particularly useful in application of LAD estimation to financial time series data.

Original languageEnglish
Pages (from-to)953-962
Number of pages10
JournalEconometric Theory
Issue number3
Publication statusPublished - 2010 Jun 1


All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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