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The MIDAS Touch: Mixed Data Sampling Regression Models

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  • Eric Ghysels
  • Pedro Santa-Clara
  • Rossen Valkanov

Abstract

We introduce Mixed Data Sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Technically speaking MIDAS models specify conditional expectations as a distributed lag of regressors recorded at some higher sampling frequencies. We examine the asymptotic properties of MIDAS regression estimation and compare it with traditional distributed lag models. MIDAS regressions have wide applicability in macroeconomics and �nance.
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Suggested Citation

  • Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    • Handle: RePEc:cir:cirwor:2004s-20
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    Keywords

    distributed log models; aliasing; discretization bias; retards échelonnés; aliasing; biais de discrétisation;
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